Lampreys (Petromyzontiformes) are an ancient group of fishes with complex life histories. We created a life cycle model that includes an R Shiny interactive web application interface to simulate abundance by life stage. This will allow scientists and managers to connect available demographic information in a framework that can be applied to questions regarding lamprey biology and conservation. We used Pacific lamprey (Entosphenus tridentatus) as a case study to highlight the utility of this model. We applied a global sensitivity analysis to explore the importance of individual life stage parameters to overall population size, and to better understand the implications of existing gaps in knowledge. We also provided example analyses of selected management scenarios (dam passage, fish translocations, and hatchery additions) influencing Pacific lamprey in fresh water. These applications illustrate how the model can be applied to inform conservation efforts. This tool will provide new capabilities for users to explore their own questions about lamprey biology and conservation. Simulations can hone hypotheses and predictions, which can then be empirically tested in the real world.
","language":"English","publisher":"PLOS","doi":"10.1371/journal.pone.0323408","usgsCitation":"Gomes, D.G., Benjamin, J.R., Clemens, B.J., Lampman, R., and Dunham, J., 2025, New technology for an ancient fish: A lamprey life cycle modeling tool with an R Shiny application: PLoS ONE, v. 20, no. 5, e0323408, 25 p., https://doi.org/10.1371/journal.pone.0323408.","productDescription":"e0323408, 25 p.","ipdsId":"IP-172919","costCenters":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"links":[{"id":489170,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0323408","text":"Publisher Index Page"},{"id":486169,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Gomes, Dylan Gerald-Everett 0000-0002-2642-3728","orcid":"https://orcid.org/0000-0002-2642-3728","contributorId":346160,"corporation":false,"usgs":true,"family":"Gomes","given":"Dylan","email":"","middleInitial":"Gerald-Everett","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":937518,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Benjamin, Joseph R. 0000-0003-3733-6838 jbenjamin@usgs.gov","orcid":"https://orcid.org/0000-0003-3733-6838","contributorId":3999,"corporation":false,"usgs":true,"family":"Benjamin","given":"Joseph","email":"jbenjamin@usgs.gov","middleInitial":"R.","affiliations":[{"id":289,"text":"Forest and Rangeland Ecosys Science Center","active":true,"usgs":true},{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":937519,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Clemens, Benjamin J.","contributorId":195098,"corporation":false,"usgs":false,"family":"Clemens","given":"Benjamin","email":"","middleInitial":"J.","affiliations":[],"preferred":false,"id":937520,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Lampman, Ralph","contributorId":215233,"corporation":false,"usgs":false,"family":"Lampman","given":"Ralph","email":"","affiliations":[],"preferred":true,"id":937521,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dunham, Jason 0000-0002-6268-0633","orcid":"https://orcid.org/0000-0002-6268-0633","contributorId":220078,"corporation":false,"usgs":true,"family":"Dunham","given":"Jason","affiliations":[{"id":290,"text":"Forest and Rangeland Ecosystem Science Center","active":false,"usgs":true}],"preferred":true,"id":937522,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267437,"text":"70267437 - 2025 - Regional analysis of the dependence of peak-flow quantiles on climate with application to adjustment to climate trends","interactions":[],"lastModifiedDate":"2025-05-23T15:07:59.713754","indexId":"70267437","displayToPublicDate":"2025-05-14T10:05:31","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":10778,"text":"Hydrology","active":true,"publicationSubtype":{"id":10}},"title":"Regional analysis of the dependence of peak-flow quantiles on climate with application to adjustment to climate trends","docAbstract":"Standard flood-frequency analysis methods rely on an assumption of stationarity, but because of growing understanding of climatic persistence and concern regarding the effects of climate change, the need for methods to detect and model nonstationary flood frequency has become widely recognized. In this study, a regional statistical method for estimating the effects of climate variations on annual maximum (peak) flows that allows for the effect to vary by quantile is presented and applied. The method uses a panel–quantile regression framework based on a location-scale model with two fixed effects per basin. The model was fitted to 330 selected gauged basins in the midwestern United States, filtered to remove basins affected by reservoir regulation and urbanization. Precipitation and discharge simulated using a water-balance model at daily and annual time scales were tested as climate variables. Annual maximum daily discharge was found to be the best predictor of peak flows, and the quantile regression coefficients were found to depend monotonically on annual exceedance probability. Application of the models to gauged basins is demonstrated by estimating the peak-flow distributions at the end of the study period (2018) and, using the panel model, to the study basins as-if-ungauged by using leave-one-out cross validation, estimating the fixed effects using static basin characteristics, and parameterizing the water-balance model discharge using median parameters. The errors of the quantiles predicted as-if-ungauged approximately doubled compared to the errors of the fitted panel model.
","language":"English","publisher":"MDPI","doi":"10.3390/hydrology12050119","usgsCitation":"Over, T.M., Marti, M.K., and Podzorski, H.L., 2025, Regional analysis of the dependence of peak-flow quantiles on climate with application to adjustment to climate trends: Hydrology, v. 12, no. 5, 119, 43 p., https://doi.org/10.3390/hydrology12050119.","productDescription":"119, 43 p.","ipdsId":"IP-167316","costCenters":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"links":[{"id":487957,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/hydrology12050119","text":"Publisher Index Page"},{"id":486509,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"12","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Over, Thomas M. 0000-0001-8280-4368","orcid":"https://orcid.org/0000-0001-8280-4368","contributorId":204650,"corporation":false,"usgs":true,"family":"Over","given":"Thomas","email":"","middleInitial":"M.","affiliations":[{"id":344,"text":"Illinois Water Science Center","active":true,"usgs":true},{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":938195,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Marti, Mackenzie K. 0000-0001-8817-4969 mmarti@usgs.gov","orcid":"https://orcid.org/0000-0001-8817-4969","contributorId":289738,"corporation":false,"usgs":true,"family":"Marti","given":"Mackenzie","email":"mmarti@usgs.gov","middleInitial":"K.","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":938196,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Podzorski, Hannah Lee 0000-0001-5204-2606 hpodzorski@usgs.gov","orcid":"https://orcid.org/0000-0001-5204-2606","contributorId":333626,"corporation":false,"usgs":true,"family":"Podzorski","given":"Hannah","email":"hpodzorski@usgs.gov","middleInitial":"Lee","affiliations":[{"id":36532,"text":"Central Midwest Water Science Center","active":true,"usgs":true}],"preferred":true,"id":938197,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70271181,"text":"70271181 - 2025 - The Hardscrabble Creek complex: A newly discovered, mostly buried, Mesoproterozoic mafic-ultramafic pluton in the Wet Mountains, Colorado, USA","interactions":[],"lastModifiedDate":"2025-09-02T14:49:24.55281","indexId":"70271181","displayToPublicDate":"2025-05-14T09:44:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1723,"text":"GSA Bulletin","active":true,"publicationSubtype":{"id":10}},"title":"The Hardscrabble Creek complex: A newly discovered, mostly buried, Mesoproterozoic mafic-ultramafic pluton in the Wet Mountains, Colorado, USA","docAbstract":"The origin of prolific ca. 1.4 Ga ferroan magmatism between the southwestern USA and eastern Canada is enigmatic and has been explained by various models, including extensional, mantle plume, and convergent plate-margin models. Rare mafic plutons are associated with the ferroan plutons, which may help constrain their mantle source and tectonic setting. In the southwestern USA, only two such mafic plutons are known to exist. We present the first evidence for a third, mostly buried, potentially layered, mafic-ultramafic Mesoproterozoic pluton, informally referred to as the Hardscrabble Creek complex, in the central Wet Mountains of Colorado, USA. Recent geophysical data show an elliptical magnetic and gravity high spatially coincident with local gabbroic outcrops. New field and petrographic analyses of these exposed rocks reveal that they consist of ultramafic to mafic cumulates, including orthopyroxenite, olivine norite, norite, and anorthosite. High-precision U-Pb dating of zircon from orthopyroxenite and norite yield weighted mean 206Pb/238U dates of 1352.36 ± 1.60 Ma and 1352.37 ± 1.71 Ma, respectively. These dates indicate that the complex formed over a narrow timeframe, after the adjacent 1362 ± 7 Ma ferroan San Isabel Granite, and during the waning stages of the regional ca. 1.4 Ga ferroan magmatism. Whole-rock geochemistry and Nd-Sr-Pb isotope compositions of samples from the Hardscrabble Creek complex are similar to those of the San Isabel Granite, suggesting that they were derived from the same or a similar mantle source. The mineral chemistry of the samples is comparable to Proterozoic massif-type anorthosites and related mafic intrusions, indicating that the Hardscrabble Creek complex and San Isabel Granite together represent a rare anorthosite-mangerite-charnockite-granite (AMCG) suite in the southwestern USA. The Hardscrabble Creek complex is unique because it formed ~80 m.y. after the other few mafic plutons in the southwestern USA, and it contains an ultramafic section that is absent from these plutons and rare to the AMCG suite in general. A combination of arc-like whole-rock geochemistry, chondrite uniform reservoir-like Nd-Sr-Pb isotopes, and ocean island basalt (OIB)-like zircon trace element chemistry suggests that the complex was derived from a partial melt of OIB-like mantle and interacted with metasomatically enriched lithospheric mantle. The enriched lithospheric mantle signature, combined with the long ~160 m.y. duration of magmatism in the region, is consistent with a period of protracted convergent tectonism.
","language":"English","publisher":"Geological Society of America","doi":"10.1130/B37903.1","usgsCitation":"Magnin, B.P., Brake, S.S., Kuiper, Y., Mohr, M.T., and Hanson, R.E., 2025, The Hardscrabble Creek complex: A newly discovered, mostly buried, Mesoproterozoic mafic-ultramafic pluton in the Wet Mountains, Colorado, USA: GSA Bulletin, v. 137, no. 9-10, p. 4558-4574, https://doi.org/10.1130/B37903.1.","productDescription":"17 p.","startPage":"4558","endPage":"4574","ipdsId":"IP-168096","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":495119,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Wet Mountains","volume":"137","issue":"9-10","noUsgsAuthors":false,"publicationDate":"2025-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Magnin, Benjamin Patrick 0000-0001-9951-4404","orcid":"https://orcid.org/0000-0001-9951-4404","contributorId":300679,"corporation":false,"usgs":true,"family":"Magnin","given":"Benjamin","email":"","middleInitial":"Patrick","affiliations":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true}],"preferred":true,"id":947668,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Brake, Sandra S.","contributorId":360805,"corporation":false,"usgs":false,"family":"Brake","given":"Sandra","middleInitial":"S.","affiliations":[{"id":17777,"text":"Indiana State University","active":true,"usgs":false}],"preferred":false,"id":947669,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Kuiper, Yvette 0000-0002-8506-8180","orcid":"https://orcid.org/0000-0002-8506-8180","contributorId":299649,"corporation":false,"usgs":false,"family":"Kuiper","given":"Yvette","email":"","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":947670,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Mohr, Michael T. 0009-0001-3814-6908","orcid":"https://orcid.org/0009-0001-3814-6908","contributorId":360807,"corporation":false,"usgs":false,"family":"Mohr","given":"Michael","middleInitial":"T.","affiliations":[{"id":16201,"text":"Boise State University","active":true,"usgs":false}],"preferred":false,"id":947671,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hanson, Richard E.","contributorId":360809,"corporation":false,"usgs":false,"family":"Hanson","given":"Richard","middleInitial":"E.","affiliations":[{"id":25471,"text":"Texas Christian University","active":true,"usgs":false}],"preferred":false,"id":947672,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266921,"text":"70266921 - 2025 - Crustal to mantle melt storage during the evolution of Hawaiian volcanoes","interactions":[],"lastModifiedDate":"2025-05-15T14:45:07.787334","indexId":"70266921","displayToPublicDate":"2025-05-14T09:42:04","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":17983,"text":"ScienceAdvances","active":true,"publicationSubtype":{"id":10}},"title":"Crustal to mantle melt storage during the evolution of Hawaiian volcanoes","docAbstract":"As the Pacific Plate migrates over the mantle plume below Hawaiʻi, magma flux decreases, resulting in changes in eruptive volume, style, and composition. It is thought that melt storage becomes deeper and ephemeral with the transition from highly voluminous tholeiitic (shield stage) to the less voluminous alkaline (post-shield and rejuvenation stages) magmatism. To quantitatively test this, we applied high-precision fluid inclusion barometry via Raman spectroscopy to samples from representative volcanoes of different evolutionary stages. This suggests an evolution from shield-stage shallow magma storage (~1 to 2 kilometers) for Kīlauea to a post-shield stage that includes crustal magma storage within the volcanic edifice (~2 kilometers) and deeper storage below the Moho (~20 to 27 kilometers) for Haleakalā. The rejuvenation stage (Diamond Head) displays mantle-dominated storage (~22 to 30 kilometers). High melt fluxes likely form stable conduits from the mantle to a shallow reservoir in the shield volcanoes. As melt flux decreases, the Moho becomes the boundary controlling melt stagnation and evolution.
","language":"English","publisher":"AAAS","doi":"10.1126/sciadv.adu9332","usgsCitation":"Gazel, E., Dayton, K., Liang, W., Hua, J., Lynn, K.J., and Hammer, J.E., 2025, Crustal to mantle melt storage during the evolution of Hawaiian volcanoes: ScienceAdvances, v. 11, no. 20, eadu9332, 9 p., https://doi.org/10.1126/sciadv.adu9332.","productDescription":"eadu9332, 9 p.","ipdsId":"IP-169266","costCenters":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":488595,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1126/sciadv.adu9332","text":"Publisher Index Page"},{"id":485992,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -154.9009775447594,\n 19.40461006158526\n ],\n [\n -156.27601944841055,\n 21.007903994893113\n ],\n [\n -158.0174647335733,\n 21.567955198381554\n ],\n [\n -158.09568568018813,\n 21.42239413562342\n ],\n [\n -156.35012350309827,\n 20.650055964686672\n ],\n [\n -155.2838484939797,\n 19.237554035059546\n ],\n [\n -154.9009775447594,\n 19.40461006158526\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","issue":"20","noUsgsAuthors":false,"publicationDate":"2025-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Gazel, Esteban","contributorId":192876,"corporation":false,"usgs":false,"family":"Gazel","given":"Esteban","email":"","affiliations":[],"preferred":false,"id":937138,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Dayton, Kyle","contributorId":355206,"corporation":false,"usgs":false,"family":"Dayton","given":"Kyle","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":937139,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Liang, Wenwei","contributorId":355207,"corporation":false,"usgs":false,"family":"Liang","given":"Wenwei","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":937140,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Hua, Junlin","contributorId":355208,"corporation":false,"usgs":false,"family":"Hua","given":"Junlin","affiliations":[{"id":16929,"text":"Brown University","active":true,"usgs":false}],"preferred":false,"id":937141,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Lynn, Kendra J. 0000-0001-7886-4376","orcid":"https://orcid.org/0000-0001-7886-4376","contributorId":290327,"corporation":false,"usgs":true,"family":"Lynn","given":"Kendra","email":"","middleInitial":"J.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":937142,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Hammer, Julia E.","contributorId":174787,"corporation":false,"usgs":false,"family":"Hammer","given":"Julia","email":"","middleInitial":"E.","affiliations":[],"preferred":false,"id":937143,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70269366,"text":"70269366 - 2025 - Genetic connectivity in a cooperatively breeding carnivore between two protected areas","interactions":[],"lastModifiedDate":"2025-07-22T13:26:31.181174","indexId":"70269366","displayToPublicDate":"2025-05-14T09:37:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Genetic connectivity in a cooperatively breeding carnivore between two protected areas","docAbstract":"Wildlife populations are increasingly threatened by human activities. Most studies, however, are often short in duration or do not encompass the large spatial extent necessary to measure the potential effects of human activities on population vital rates. Furthermore, the life history features of species with high fecundity and excellent dispersal capabilities can act as buffers against the potential negative effects of human activities on their populations. We used a 30-year dataset of genetic samples from gray wolves (Canis lupus) in Alaska, USA, to examine genetic connectivity and diversity between National Park units separated by a region with recurrent human-caused mortality. We found that the two protected populations were genetically similar and that dispersal events occurred between them even though they are > 450 km apart. We posit that intact ecosystems and a history of continuous distribution of wolves surrounding the affected regions likely maintained the genetic connectivity of wolves in the two protected areas.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.71420","usgsCitation":"Cerreta, A., Adams, J., Borg, B., Sorum, M., Waits, L., and Ausband, D.E., 2025, Genetic connectivity in a cooperatively breeding carnivore between two protected areas: Ecology and Evolution, v. 15, no. 5, e71420, 10 p., https://doi.org/10.1002/ece3.71420.","productDescription":"e71420, 10 p.","ipdsId":"IP-158851","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":492874,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71420","text":"Publisher Index Page"},{"id":492626,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Denali National Park and Preserve, Yukon- Charley Rivers National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -148.7512872450975,\n 64.07437550215425\n ],\n [\n -153.00052847916817,\n 64.07437550215425\n ],\n [\n -153.00052847916817,\n 62.276194894069874\n ],\n [\n -148.7512872450975,\n 62.276194894069874\n ],\n [\n -148.7512872450975,\n 64.07437550215425\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -141.0182219902975,\n 65.5653487163298\n ],\n [\n -144.37903864723086,\n 65.5653487163298\n ],\n [\n -144.37903864723086,\n 64.4468015781325\n ],\n [\n -141.0182219902975,\n 64.4468015781325\n ],\n [\n -141.0182219902975,\n 65.5653487163298\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Cerreta, Ariana L.","contributorId":358318,"corporation":false,"usgs":false,"family":"Cerreta","given":"Ariana L.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":943537,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Adams, Jennifer R.","contributorId":358321,"corporation":false,"usgs":false,"family":"Adams","given":"Jennifer R.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":943539,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Borg, Bridget L.","contributorId":358323,"corporation":false,"usgs":false,"family":"Borg","given":"Bridget L.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":943540,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Sorum, Mathew S.","contributorId":358326,"corporation":false,"usgs":false,"family":"Sorum","given":"Mathew S.","affiliations":[{"id":36189,"text":"National Park Service","active":true,"usgs":false}],"preferred":false,"id":943541,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Waits, Lisette P.","contributorId":358329,"corporation":false,"usgs":false,"family":"Waits","given":"Lisette P.","affiliations":[{"id":36394,"text":"University of Idaho","active":true,"usgs":false}],"preferred":false,"id":943542,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Ausband, David Edward 0000-0001-9204-9837","orcid":"https://orcid.org/0000-0001-9204-9837","contributorId":275329,"corporation":false,"usgs":true,"family":"Ausband","given":"David","email":"","middleInitial":"Edward","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":943538,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70269288,"text":"70269288 - 2025 - Controls on water quality below a reclaimed surface coal mine, southeastern Montana","interactions":[],"lastModifiedDate":"2025-07-17T14:06:57.223082","indexId":"70269288","displayToPublicDate":"2025-05-14T08:59:38","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1923,"text":"Hydrogeology Journal","active":true,"publicationSubtype":{"id":10}},"title":"Controls on water quality below a reclaimed surface coal mine, southeastern Montana","docAbstract":"Coal mining and reclamation can have a profound influence on hydrogeologic systems, with clear consequences for groundwater quality, yet their long-term influence on downgradient water quality over time following reclamation is less well documented. Geochemical trends were evaluated in water quality downgradient of a fully reclaimed landscape at the former Big Sky Mine in the Rosebud Creek watershed (southeastern Montana, USA), over a 3-year period (2020–2022), including bond release in 2022. Within 6 km downgradient from the reclaimed area, sulfate concentrations decreased from approximately 3500 to 1800 mg l−1 within the Miller Coulee alluvial aquifer. Major ions, δ34SSO4 values, and residence time tracers suggest that the observed decreases in sulfate concentration result from a combination of dilution by mixed-age inflows and incomplete transit of the high salinity plume from the mine boundary. Both bedrock and alluvial aquifers of the Rosebud Creek corridor contained contributions of millennia-old regional groundwater, which may serve to mitigate mine-derived high salinity waters. Rosebud Creek, which traverses the outflow zone of Miller Coulee in the study area, exhibited high sulfate concentrations during low flows and consistent downgradient increases in sulfate concentration. The possibility of plume dynamics in Miller Coulee suggests that the greatest water quality impacts may not yet have reached Rosebud Creek.
","language":"English","publisher":"Springer","doi":"10.1007/s10040-025-02898-z","usgsCitation":"Keeshin, S., Ewing, S., Meredith, E., Payne, R.A., Gardner, W.P., and Hunt, A.G., 2025, Controls on water quality below a reclaimed surface coal mine, southeastern Montana: Hydrogeology Journal, v. 33, p. 715-737, https://doi.org/10.1007/s10040-025-02898-z.","productDescription":"23 p.","startPage":"715","endPage":"737","ipdsId":"IP-169829","costCenters":[{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":492507,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1007/s10040-025-02898-z","text":"Publisher Index Page"},{"id":492414,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Montana","otherGeospatial":"Powder River basin","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.76252916407701,\n 45.96424654184909\n ],\n [\n -106.76252916407701,\n 45.71193610632727\n ],\n [\n -106.38940057072405,\n 45.71193610632727\n ],\n [\n -106.38940057072405,\n 45.96424654184909\n ],\n [\n -106.76252916407701,\n 45.96424654184909\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"33","noUsgsAuthors":false,"publicationDate":"2025-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Keeshin, Skye 0009-0009-8644-9872","orcid":"https://orcid.org/0009-0009-8644-9872","contributorId":358243,"corporation":false,"usgs":false,"family":"Keeshin","given":"Skye","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":943360,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Ewing, Stephanie A. 0000-0003-0713-4266","orcid":"https://orcid.org/0000-0003-0713-4266","contributorId":358244,"corporation":false,"usgs":false,"family":"Ewing","given":"Stephanie A.","affiliations":[{"id":36555,"text":"Montana State University","active":true,"usgs":false}],"preferred":false,"id":943361,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Meredith, Elizabeth B","contributorId":358247,"corporation":false,"usgs":false,"family":"Meredith","given":"Elizabeth B","affiliations":[{"id":36941,"text":"Montana Bureau of Mines and Geology","active":true,"usgs":false}],"preferred":false,"id":943362,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Payne, Robert A.","contributorId":179214,"corporation":false,"usgs":false,"family":"Payne","given":"Robert","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":943363,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gardner, W. 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We use geospatial tools to estimate the lengths and percentages of total length of roads in landslide-susceptible areas and differentiate results by road type, jurisdiction, and susceptibility level. We summarize traffic-volume counts in landslide-susceptible areas in terms of annual and maximum hourly counts using geospatial zones based on the concept of stopping-sight distances. A substantial percentage of the U.S. road network is in areas with some level of landslide susceptibility from 35 % (by length) of all roads to 68 % of county routes. Several Interstate highways have considerable lengths of road in areas with highest landslide susceptibility. There are hundreds of sites with high hourly and annual traffic volumes in areas of highest landslide susceptibility, indicating potential threats to life safety and traffic disruption.
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Center","active":true,"usgs":true}],"preferred":true,"id":941501,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70267270,"text":"70267270 - 2025 - Flexible phenology of a C4 grass linked to resiliency to seasonal and multiyear drought events in the American southwest","interactions":[],"lastModifiedDate":"2025-05-19T15:26:06.808659","indexId":"70267270","displayToPublicDate":"2025-05-14T08:21:51","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1467,"text":"Ecology and Evolution","active":true,"publicationSubtype":{"id":10}},"title":"Flexible phenology of a C4 grass linked to resiliency to seasonal and multiyear drought events in the American southwest","docAbstract":"Rising temperatures are predicted to further limit dryland water availability as droughts become more intense and frequent and seasonal precipitation patterns shift. Vegetation drought stress may increase mortality and cause declines and delays in phenological events, thereby impacting species' capacity to persist and recover from extreme drought conditions. We compare phenological responses of two common dryland perennial grass species, Achnatherum hymenoides (C3) and Pleuraphis jamesii (C4), to 4 years of experimentally imposed precipitation drought treatments (cool season, warm season, ambient), followed by 2 years of recovery on the Colorado Plateau, United States of America. Tagged individual grasses from both species were monitored biweekly and assessed for phenological metrics and mortality. The C3 grass exhibited less phenological flexibility to both seasonal and interannual drought conditions and experienced high rates of mortality, thus reducing resiliency. Conversely, the C4 grass showed more phenological plasticity during imposed drought treatments, with treatment effects diminishing in the two-year recovery period during a severe ambient drought. Synthesis: Results suggest that plant photosynthetic strategies may impact plant resistance and resiliency to drought. Here, C3 grass populations may decline, potentially shifting cool dryland ecosystems into a system comprised predominantly of warm-season adapted species.
","language":"English","publisher":"Wiley","doi":"10.1002/ece3.71435","usgsCitation":"Finger-Higgens, R.A., Hoover, D.L., Knight, A.C., Schlaepfer, D.R., and Duniway, M.C., 2025, Flexible phenology of a C4 grass linked to resiliency to seasonal and multiyear drought events in the American southwest: Ecology and Evolution, v. 15, no. 5, e71435, 12 p., https://doi.org/10.1002/ece3.71435.","productDescription":"e71435, 12 p.","ipdsId":"IP-175217","costCenters":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"links":[{"id":490133,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ece3.71435","text":"Publisher Index Page"},{"id":486311,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P13YQBFB","text":"USGS data release","linkHelpText":"Plant community composition, abundance, phenology, and soil data from a four-year seasonal drought experiment followed by four years of recovery in a mixed grassland on the Colorado Plateau"},{"id":486158,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Utah","otherGeospatial":"Colorado Plateau, southeastern Utah","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -111.13988247197315,\n 38.391364084093055\n ],\n [\n -111.13988247197315,\n 36.98964710801718\n ],\n [\n -109.03982788793104,\n 36.98964710801718\n ],\n [\n -109.03982788793104,\n 38.391364084093055\n ],\n [\n -111.13988247197315,\n 38.391364084093055\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"15","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Finger-Higgens, Rebecca A 0000-0002-7645-504X","orcid":"https://orcid.org/0000-0002-7645-504X","contributorId":290211,"corporation":false,"usgs":true,"family":"Finger-Higgens","given":"Rebecca","email":"","middleInitial":"A","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":937552,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Hoover, David L. dlhoover@usgs.gov","contributorId":245331,"corporation":false,"usgs":false,"family":"Hoover","given":"David","email":"dlhoover@usgs.gov","middleInitial":"L.","affiliations":[{"id":49151,"text":"USDA-ARS Rangeland Resources Research Unit, Crops Research Laboratory, Fort Collins, CO","active":true,"usgs":false}],"preferred":false,"id":937553,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Knight, Anna C. 0000-0002-9455-2855","orcid":"https://orcid.org/0000-0002-9455-2855","contributorId":255113,"corporation":false,"usgs":true,"family":"Knight","given":"Anna","email":"","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":937554,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Schlaepfer, Daniel Rodolphe 0000-0001-9973-2065","orcid":"https://orcid.org/0000-0001-9973-2065","contributorId":225569,"corporation":false,"usgs":true,"family":"Schlaepfer","given":"Daniel","email":"","middleInitial":"Rodolphe","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":937555,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Duniway, Michael C. 0000-0002-9643-2785 mduniway@usgs.gov","orcid":"https://orcid.org/0000-0002-9643-2785","contributorId":4212,"corporation":false,"usgs":true,"family":"Duniway","given":"Michael","email":"mduniway@usgs.gov","middleInitial":"C.","affiliations":[{"id":568,"text":"Southwest Biological Science Center","active":true,"usgs":true}],"preferred":true,"id":937556,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267215,"text":"70267215 - 2025 - Paleo-scours within the layered sulfate-bearing unit at Gale crater, Mars: Evidence for intense wind erosion","interactions":[],"lastModifiedDate":"2025-05-20T13:19:43.188052","indexId":"70267215","displayToPublicDate":"2025-05-14T08:15:31","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9967,"text":"JGR Planets","active":true,"publicationSubtype":{"id":10}},"title":"Paleo-scours within the layered sulfate-bearing unit at Gale crater, Mars: Evidence for intense wind erosion","docAbstract":"The surface of modern Mars is largely shaped by wind, but the influence of past wind activity is less well constrained. Sedimentary rocks exposed in the lower foothills of Aeolis Mons, the central mound within Gale crater, record a transition from predominantly lacustrine deposition in the Murray formation to aeolian deposition in the Mirador formation. Here, we report a series of enigmatic decameter-wide, concave-up scour-and-fill structures within the Mirador formation and discuss their formation mechanisms. Using panoramic images of stratigraphy exposed in cliff faces acquired by the Curiosity rover, we map the extent, distribution and orientation of the scour-and-fill structures and document the sedimentary facies within and surrounding these structures. The scours are grouped into two classes: (A) scours with a simple, symmetric morphology and light-toned, draping infill; and (B) scours with lateral pinching and dark-toned infill. We find that the scour-enclosing environment is composed of planar, even-in-thickness laminations with a pin-stripe pattern which we interpret as wind-ripple strata formed within an aeolian sandsheet environment. Class B contains cm-scale cross-bedding and a wing-shaped feature making this scour-and-fill structure consistent with fluvial processes. We interpret scour fill of class A as an aeolian infill due to similarities with the surrounding sandsheet strata. The broad morphologies and distribution of class A are also consistent with the geometry of blowout structures formed by localized, enhanced wind deflation. These paleo-blowout structures occur clustered within the same stratigraphic interval, which may imply that they record an interval of intensified wind activity at Gale crater.","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2024JE008680","usgsCitation":"Roberts, A., Gupta, S., Banhan, S., Cowart, A., Edgar, L.A., Rapin, W., Dietrich, W., Kite, E., Davis, J., Caravaca, G., Mondro, C., Gasda, P., Johnson, J., Le Mouelic, S., Fey, D., Bryk, A., Paar, G., Harris, R., Fraeman, A., and Vasavada, A., 2025, Paleo-scours within the layered sulfate-bearing unit at Gale crater, Mars: Evidence for intense wind erosion: JGR Planets, v. 130, no. 5, e2024JE008680, 32 p., https://doi.org/10.1029/2024JE008680.","productDescription":"e2024JE008680, 32 p.","ipdsId":"IP-169999","costCenters":[{"id":131,"text":"Astrogeology Science Center","active":true,"usgs":true}],"links":[{"id":489183,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2024je008680","text":"Publisher Index Page"},{"id":486069,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Gale Crater, Mars","volume":"130","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Roberts, A.L.","contributorId":355429,"corporation":false,"usgs":false,"family":"Roberts","given":"A.L.","affiliations":[{"id":84748,"text":"Department of Earth Science & Engineering, Imperial College London","active":true,"usgs":false}],"preferred":false,"id":937306,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Gupta, S.","contributorId":177658,"corporation":false,"usgs":false,"family":"Gupta","given":"S.","email":"","affiliations":[],"preferred":false,"id":937307,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Banhan, S.G.","contributorId":355430,"corporation":false,"usgs":false,"family":"Banhan","given":"S.G.","affiliations":[{"id":84748,"text":"Department of Earth Science & Engineering, Imperial College London","active":true,"usgs":false}],"preferred":false,"id":937308,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cowart, A.","contributorId":355431,"corporation":false,"usgs":false,"family":"Cowart","given":"A.","affiliations":[{"id":13179,"text":"Planetary Science Institute","active":true,"usgs":false}],"preferred":false,"id":937309,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Edgar, Lauren A. 0000-0001-7512-7813 ledgar@usgs.gov","orcid":"https://orcid.org/0000-0001-7512-7813","contributorId":167501,"corporation":false,"usgs":true,"family":"Edgar","given":"Lauren","email":"ledgar@usgs.gov","middleInitial":"A.","affiliations":[{"id":131,"text":"Astrogeology Science 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A.B.","contributorId":351718,"corporation":false,"usgs":false,"family":"Bryk","given":"A.B.","affiliations":[{"id":36942,"text":"University of California, Berkeley","active":true,"usgs":false}],"preferred":false,"id":937323,"contributorType":{"id":1,"text":"Authors"},"rank":16},{"text":"Paar, G.","contributorId":252879,"corporation":false,"usgs":false,"family":"Paar","given":"G.","email":"","affiliations":[{"id":50456,"text":"Joanneum Research, Graz, Austria","active":true,"usgs":false}],"preferred":false,"id":937395,"contributorType":{"id":1,"text":"Authors"},"rank":17},{"text":"Harris, R.A.","contributorId":355436,"corporation":false,"usgs":false,"family":"Harris","given":"R.A.","affiliations":[{"id":84750,"text":"Department of Earth Sciences, Natural History Museum, London","active":true,"usgs":false}],"preferred":false,"id":937324,"contributorType":{"id":1,"text":"Authors"},"rank":18},{"text":"Fraeman, A.","contributorId":177657,"corporation":false,"usgs":false,"family":"Fraeman","given":"A.","affiliations":[],"preferred":false,"id":937325,"contributorType":{"id":1,"text":"Authors"},"rank":19},{"text":"Vasavada, A.R.","contributorId":351725,"corporation":false,"usgs":false,"family":"Vasavada","given":"A.R.","affiliations":[{"id":36392,"text":"Jet Propulsion Laboratory","active":true,"usgs":false}],"preferred":false,"id":937326,"contributorType":{"id":1,"text":"Authors"},"rank":20}]}} ,{"id":70267239,"text":"70267239 - 2025 - Environmental persistence and toxicity of weathered wildland fire retardants to rainbow trout","interactions":[],"lastModifiedDate":"2025-06-12T15:55:21.026427","indexId":"70267239","displayToPublicDate":"2025-05-14T08:09:25","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":887,"text":"Archives of Environmental Contamination and Toxicology","active":true,"publicationSubtype":{"id":10}},"title":"Environmental persistence and toxicity of weathered wildland fire retardants to rainbow trout","docAbstract":"Long-term fire retardants are employed to combat and control wildfires by altering the way fuels burn, and they continue to decrease fire intensity after water in the retardant solution has evaporated. After application, fire retardants may persist on dry stream beds or in riparian habitats before precipitation events flush the retardant into intermittent streams. We exposed juvenile (30–60 days post swim-up) rainbow trout (Oncorhynchus mykiss) to fire retardants weathered for 7–56 days on different substrates (duff, gravel, high organic content soil, and low organic content soil) under static conditions for 96 h to evaluate the potential toxicity of two current-use long-term fire-retardant (LC95A-R and MVP-Fx) products. Trout mortality was greater in LC95A-R treatments compared to MVP-Fx due to higher concentrations of LC95A-R in the applied product than MVP-Fx at the same application rate. Underlying substrate affected fire-retardant toxicity, with 31% higher average mortality for products applied to duff and gravel compared to soil. Differences in mortality across substrates and products after weathering may be attributed to differences in the mix ratio of applied product and interactions of product chemistries with underlying substrate. These interactions resulted in elevated ionic concentrations of the overlying water in duff and gravel treatments. Trout mortality decreased 15% for products weathered 56 days compared to 7 days. Our results suggest that long-term fire retardants may persist in the environment and that underlying substrate may alter the toxicity of these products upon entrance into an intermittent stream.
","language":"English","publisher":"Springer Nature","doi":"10.1007/s00244-025-01131-y","usgsCitation":"Mackey, C.M., Iacchetta, M.G., and Puglis, H.J., 2025, Environmental persistence and toxicity of weathered wildland fire retardants to rainbow trout: Archives of Environmental Contamination and Toxicology, v. 88, p. 397-406, https://doi.org/10.1007/s00244-025-01131-y.","productDescription":"10 p.","startPage":"397","endPage":"406","ipdsId":"IP-161555","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":486156,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"88","noUsgsAuthors":false,"publicationDate":"2025-05-14","publicationStatus":"PW","contributors":{"authors":[{"text":"Mackey, Christina M. 0000-0003-1737-2698","orcid":"https://orcid.org/0000-0003-1737-2698","contributorId":243574,"corporation":false,"usgs":true,"family":"Mackey","given":"Christina","email":"","middleInitial":"M.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":937424,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Iacchetta, Michael G. 0000-0001-9459-1435","orcid":"https://orcid.org/0000-0001-9459-1435","contributorId":291394,"corporation":false,"usgs":true,"family":"Iacchetta","given":"Michael","email":"","middleInitial":"G.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":937425,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Puglis, Holly J. 0000-0002-3090-6597 hpuglis@usgs.gov","orcid":"https://orcid.org/0000-0002-3090-6597","contributorId":4686,"corporation":false,"usgs":true,"family":"Puglis","given":"Holly","email":"hpuglis@usgs.gov","middleInitial":"J.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":937426,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ,{"id":70266866,"text":"ofr20251025 - 2025 - Distribution and abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) at the Mojave River Dam, San Bernardino County, California—2024 data summary","interactions":[],"lastModifiedDate":"2025-05-14T14:24:51.77589","indexId":"ofr20251025","displayToPublicDate":"2025-05-13T11:29:37","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1025","displayTitle":"Distribution and Abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) at the Mojave River Dam, San Bernardino County, California—2024 Data Summary","title":"Distribution and abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) at the Mojave River Dam, San Bernardino County, California—2024 data summary","docAbstract":"We surveyed for Least Bell’s Vireos (Vireo bellii pusillus; vireo) and Southwestern Willow Flycatchers (Empidonax traillii extimus; flycatcher) at the Mojave River Dam study area near Hesperia, California, in 2024. Four vireo surveys were completed between April 17 and July 2, 2024, and three flycatcher surveys were completed between May 23 and July 2, 2024.
We detected three territorial male vireos, all of which were paired. No juveniles were observed during surveys. Vireo territories were reported in two habitat types: riparian scrub and willow-cottonwood. Red or arroyo willow (Salix laevigata or lasiolepis) was the dominant plant species in most vireo territories. No territorial or transient flycatchers were observed.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251025","programNote":"Ecosystems Mission Area—Species Management Research Program","usgsCitation":"Howell, S.L., and Kus, B.E., 2025, Distribution and abundance of Least Bell’s Vireos (Vireo bellii pusillus) and Southwestern Willow Flycatchers (Empidonax traillii extimus) at the Mojave River Dam, San Bernardino County, California—2024 data summary: U.S. Geological Survey Open-File Report 2025–1025, 8 p., https://doi.org/10.3133/ofr20251025.","productDescription":"vi, 8 p.","onlineOnly":"Y","ipdsId":"IP-172384","costCenters":[{"id":651,"text":"Western Ecological Research Center","active":true,"usgs":true}],"links":[{"id":485895,"rank":5,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1025/ofr20251025.XML"},{"id":485894,"rank":4,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1025/images"},{"id":485893,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251025/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1025"},{"id":485892,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1025/ofr20251025.pdf","text":"Report","size":"1.9 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1025"},{"id":485891,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1025/coverthb.jpg"}],"country":"United States","state":"California","county":"San Bernardino County","otherGeospatial":"Mojave River Dam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -117.2768615020681,\n 34.370295162773715\n ],\n [\n -117.2768615020681,\n 34.31872800675019\n ],\n [\n -117.21059336313478,\n 34.31872800675019\n ],\n [\n -117.21059336313478,\n 34.370295162773715\n ],\n [\n -117.2768615020681,\n 34.370295162773715\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"Director, Western Ecological Research Center
U.S. Geological Survey
3020 State University Drive East
Sacramento, California 95819
Reliable population estimates are one of the most elementary needs for the management of wildlife, particularly for introduced ungulates on oceanic islands. We aimed to produce accurate and precise density estimates of Philippine deer (Rusa marianna) and wild pigs (Sus scrofa) on Guam using motion-triggered cameras combined with distance sampling to estimate densities from observations of unmarked animals while accounting for imperfect detection. We used an automated digital data processing pipeline for species recognition and to estimate the distance to detected species. Our density estimates were slightly lower than published estimates, consistent with management to reduce populations. We estimated the number of camera traps needed to obtain a 0.1 coefficient of variation was substantial, requiring > ten-fold increase in camera traps, while estimates with precision of 0.2 or 0.3 were more achievable, requiring doubling to quadrupling the number of camera traps. We provide best practices for establishing and conducting distance sampling with camera trap surveys for density estimation based on lessons learned during this study. Future studies should consider distance sampling with camera traps to efficiently survey and monitor unmarked animals, particularly medium-sized ungulates, in tropical, oceanic island ecosystems.
","language":"English","publisher":"Cambridge University Press","doi":"10.1017/S0266467425000033","usgsCitation":"Camp, R.J., Bak, T.M., Burt, M., and Vogt, S., 2025, Using distance sampling with camera traps to estimate densities of ungulates on tropical oceanic islands: Journal of Tropical Ecology, v. 41, e12, https://doi.org/10.1017/S0266467425000033.","productDescription":"e12","ipdsId":"IP-154449","costCenters":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true}],"links":[{"id":486578,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"otherGeospatial":"Guam","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 144.96784988323265,\n 13.61173385872614\n ],\n [\n 144.8366796899819,\n 13.68869399233894\n ],\n [\n 144.63621203614423,\n 13.440889342095488\n ],\n [\n 144.62136258030552,\n 13.248242573805925\n ],\n [\n 144.72778368049006,\n 13.221741661313231\n ],\n [\n 144.79955605038276,\n 13.274740600770016\n ],\n [\n 144.81688041552877,\n 13.419224264484484\n ],\n [\n 144.96042515531252,\n 13.525123785236971\n ],\n [\n 144.96784988323265,\n 13.61173385872614\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"41","noUsgsAuthors":false,"publicationDate":"2025-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Camp, Richard J. 0000-0001-7008-923X rick_camp@usgs.gov","orcid":"https://orcid.org/0000-0001-7008-923X","contributorId":189964,"corporation":false,"usgs":true,"family":"Camp","given":"Richard","email":"rick_camp@usgs.gov","middleInitial":"J.","affiliations":[{"id":521,"text":"Pacific Island Ecosystems Research Center","active":false,"usgs":true},{"id":5049,"text":"Pacific Islands Ecosys Research Center","active":true,"usgs":true}],"preferred":true,"id":938391,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Bak, Trevor M.","contributorId":317824,"corporation":false,"usgs":false,"family":"Bak","given":"Trevor","email":"","middleInitial":"M.","affiliations":[{"id":13341,"text":"Hawai‘i Cooperative Studies Unit, University of Hawai‘i at Hilo","active":true,"usgs":false}],"preferred":false,"id":938392,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Burt, Matthew D","contributorId":355925,"corporation":false,"usgs":false,"family":"Burt","given":"Matthew D","affiliations":[{"id":84860,"text":"Naval Facilities Marianas","active":true,"usgs":false}],"preferred":false,"id":938393,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Vogt, Scott","contributorId":355926,"corporation":false,"usgs":false,"family":"Vogt","given":"Scott","affiliations":[{"id":84860,"text":"Naval Facilities Marianas","active":true,"usgs":false}],"preferred":false,"id":938394,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70267370,"text":"70267370 - 2025 - Fine-resolution satellite remote sensing improves spatially distributed snow modeling to near real time","interactions":[],"lastModifiedDate":"2025-05-21T14:36:05.59686","indexId":"70267370","displayToPublicDate":"2025-05-13T09:30:10","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3250,"text":"Remote Sensing","active":true,"publicationSubtype":{"id":10}},"title":"Fine-resolution satellite remote sensing improves spatially distributed snow modeling to near real time","docAbstract":"Given the highly variable distribution of seasonal snowpacks in complex mountainous environments, the accurate snow modeling of basin-wide snow water equivalent (SWE) requires a spatially distributed approach at a sufficiently fine grid resolution (<500 m) to account for the important processes in the seasonal evolution of a snowpack (e.g., wind redistribution of snow to resolve patchy snow cover in an alpine zone). However, even well-validated snow evolution models, such as SnowModel, are prone to errors when key model inputs, such as the precipitation and wind speed and direction, are inaccurate or only available at coarse spatial resolutions. Incorporating fine-spatial-resolution remotely sensed snow-covered area (SCA) information into spatially distributed snow modeling has the potential to refine and improve fine-resolution snow water equivalent (SWE) estimates. This study developed 30 m resolution SnowModel simulations across the Big Thompson River, Fraser River, Three Lakes, and Willow Creek Basins, a total area of 4212 km2 in Colorado, for the water years 2000–2023, and evaluated the incorporation of a Moderate Resolution Imaging Spectroradiometer (MODIS) and Landsat SCA datasets into the model’s development and calibration. The SnowModel was calibrated spatially to the Landsat mean annual snow persistence (SP) and temporally to the MODIS mean basin SCA using a multi-objective calibration procedure executed using Latin hypercube sampling and a stepwise calibration process. The Landsat mean annual SP was also used to further optimize the SnowModel simulations through the development of a spatially variable precipitation correction field. The evaluations of the SnowModel simulations using the Airborne Snow Observatories’ (ASO’s) light detection and ranging (lidar)-derived SWE estimates show that the versions of the SnowModel calibrated to the remotely sensed SCA had an improved performance (mean error ranging from −28 mm to −6 mm) compared with the baseline simulations (mean error ranging from 69 mm to 86 mm), and comparable spatial patterns to those of the ASO, especially at the highest elevations. Furthermore, this study’s results highlight how a regularly updated 30 m resolution SCA could be used to further improve the calibrated SnowModel simulations to near real time (latency of 5 days or less).
","language":"English","publisher":"MDPI","doi":"10.3390/rs17101704","usgsCitation":"Sexstone, G., Akie, G.A., Selkowitz, D.J., Barnhart, T., Rey, D., León-Salazar, C., Carbone, E., and Bearup, L.A., 2025, Fine-resolution satellite remote sensing improves spatially distributed snow modeling to near real time: Remote Sensing, v. 17, no. 10, 1704, 24 p., https://doi.org/10.3390/rs17101704.","productDescription":"1704, 24 p.","ipdsId":"IP-174585","costCenters":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true},{"id":685,"text":"Wyoming-Montana Water Science Center","active":false,"usgs":true},{"id":37786,"text":"WMA - Observing Systems Division","active":true,"usgs":true}],"links":[{"id":490140,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.3390/rs17101704","text":"Publisher Index Page"},{"id":486286,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"Rocky Mountains","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.33,\n 40.85\n ],\n [\n -106.33,\n 39.65\n ],\n [\n -105.17,\n 39.65\n ],\n [\n -105.17,\n 40.85\n ],\n [\n -106.33,\n 40.85\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"17","issue":"10","noUsgsAuthors":false,"publicationDate":"2025-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Sexstone, Graham A. 0000-0001-8913-0546","orcid":"https://orcid.org/0000-0001-8913-0546","contributorId":203850,"corporation":false,"usgs":true,"family":"Sexstone","given":"Graham A.","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":938011,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Akie, Garrett Alexander 0000-0002-6356-7106","orcid":"https://orcid.org/0000-0002-6356-7106","contributorId":290236,"corporation":false,"usgs":true,"family":"Akie","given":"Garrett","email":"","middleInitial":"Alexander","affiliations":[{"id":191,"text":"Colorado Water Science Center","active":true,"usgs":true}],"preferred":true,"id":938012,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Selkowitz, David J. 0000-0003-0824-7051 dselkowitz@usgs.gov","orcid":"https://orcid.org/0000-0003-0824-7051","contributorId":3259,"corporation":false,"usgs":true,"family":"Selkowitz","given":"David","email":"dselkowitz@usgs.gov","middleInitial":"J.","affiliations":[{"id":114,"text":"Alaska Science Center","active":true,"usgs":true},{"id":118,"text":"Alaska Science Center Geography","active":true,"usgs":true}],"preferred":true,"id":938013,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Barnhart, Theodore B. 0000-0002-9682-3217","orcid":"https://orcid.org/0000-0002-9682-3217","contributorId":202558,"corporation":false,"usgs":true,"family":"Barnhart","given":"Theodore B.","affiliations":[{"id":5050,"text":"WY-MT Water Science Center","active":true,"usgs":true}],"preferred":true,"id":938014,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Rey, David M. 0000-0003-2629-365X","orcid":"https://orcid.org/0000-0003-2629-365X","contributorId":211848,"corporation":false,"usgs":true,"family":"Rey","given":"David M.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true}],"preferred":true,"id":938015,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"León-Salazar, Claudia","contributorId":355707,"corporation":false,"usgs":false,"family":"León-Salazar","given":"Claudia","affiliations":[{"id":6736,"text":"Bureau of Reclamation","active":true,"usgs":false}],"preferred":false,"id":938016,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Carbone, Emily","contributorId":355708,"corporation":false,"usgs":false,"family":"Carbone","given":"Emily","affiliations":[{"id":84819,"text":"Northern Water","active":true,"usgs":false}],"preferred":false,"id":938017,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Bearup, Lindsay A.","contributorId":139257,"corporation":false,"usgs":false,"family":"Bearup","given":"Lindsay","email":"","middleInitial":"A.","affiliations":[{"id":6606,"text":"Colorado School of Mines","active":true,"usgs":false}],"preferred":false,"id":938018,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70268342,"text":"70268342 - 2025 - Shifting baselines of coral-reef species composition from the Late Pleistocene to the present in the Florida Keys","interactions":[],"lastModifiedDate":"2025-06-23T14:20:17.616459","indexId":"70268342","displayToPublicDate":"2025-05-13T09:14:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5781,"text":"The Depositional Record","active":true,"publicationSubtype":{"id":10}},"title":"Shifting baselines of coral-reef species composition from the Late Pleistocene to the present in the Florida Keys","docAbstract":"The ongoing global-scale reassembly of modern coral reefs is unprecedented compared with the observed stability of most late Quaternary reef assemblages. One notable exception is the marine isotope stage (MIS) 5e (ca 130–116 thousand years ago [ka]) reefs in the Florida Keys, where the ubiquitous shallow-water coral, Acropora palmata, was near absent. Little is known, however, about reefs that grew during MIS5d–a (ca 116–74 ka), between MIS5e and the Holocene. It is therefore unclear whether Florida's unique MIS5e coral assemblages represent a geologically brief anomaly or a more persistent departure from the western Atlantic coral-reef archetype. We addressed that question by reconstructing the composition of MIS5d–a reefs within 29 coral-reef cores collected throughout the Florida Keys. We then compared the relative composition of corals during MIS5d–a to existing datasets from MIS5e, Holocene and modern (1996 and 2022) reefs to evaluate how far today's reef assemblages have diverged from geological baselines. We show that although the proportion of reef frameworks built by corals was remarkably consistent (ca 38%), species composition changed significantly through time. Acropora palmata was rare throughout MIS5, which we hypothesise was due to greater cold-temperature stress in Florida's subtropical reefs compared with the more climatically stable tropics. In contrast, the massive reef-building coral, Orbicella spp., was regionally dominant throughout the late Quaternary, but has become increasingly rare on modern reefs. By 2022, reefs in the Florida Keys were characterised by a truly novel coral assemblage dominated by Porites astreoides and Siderastrea siderea. In many ways, Florida's reefs defy the concept of a natural baseline; instead, their most persistent characteristic since the Late Pleistocene is their uniqueness. Yet, as reefs are increasingly subjected to unprecedented levels of environmental change, the exceptions to what was normal in the past could, paradoxically, provide the best geological analogues for the future.
","language":"English","publisher":"WIley","doi":"10.1002/dep2.70009","usgsCitation":"Toth, L., Stathakopoulos, A., Hsia, S., and Weinstein, D.A., 2025, Shifting baselines of coral-reef species composition from the Late Pleistocene to the present in the Florida Keys: The Depositional Record, v. 11, no. 3, p. 893-916, https://doi.org/10.1002/dep2.70009.","productDescription":"24 p.","startPage":"893","endPage":"916","ipdsId":"IP-173487","costCenters":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true},{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"links":[{"id":491456,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/dep2.70009","text":"Publisher Index Page"},{"id":491097,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Florida","otherGeospatial":"Florida Keys","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -80.17917140030995,\n 25.383351188271973\n ],\n [\n -81.59701661611159,\n 24.90866922937429\n ],\n [\n -83.02465696293855,\n 24.77579446049141\n ],\n [\n -83.06138870428032,\n 24.366054515738625\n ],\n [\n -81.8345485434568,\n 24.395013657422012\n ],\n [\n -80.65178647224371,\n 24.557720553123204\n ],\n [\n -80.17917140030995,\n 25.383351188271973\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"11","issue":"3","noUsgsAuthors":false,"publicationDate":"2025-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Toth, Lauren T. 0000-0002-2568-802X ltoth@usgs.gov","orcid":"https://orcid.org/0000-0002-2568-802X","contributorId":181748,"corporation":false,"usgs":true,"family":"Toth","given":"Lauren","email":"ltoth@usgs.gov","middleInitial":"T.","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940869,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Stathakopoulos, Anastasios 0000-0002-4404-035X astathakopoulos@usgs.gov","orcid":"https://orcid.org/0000-0002-4404-035X","contributorId":147744,"corporation":false,"usgs":true,"family":"Stathakopoulos","given":"Anastasios","email":"astathakopoulos@usgs.gov","affiliations":[{"id":574,"text":"St. Petersburg Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940870,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Hsia, Scarlette Shan-Hwei 0000-0002-2230-9004","orcid":"https://orcid.org/0000-0002-2230-9004","contributorId":346523,"corporation":false,"usgs":true,"family":"Hsia","given":"Scarlette Shan-Hwei","affiliations":[{"id":40020,"text":"Florence Bascom Geoscience Center","active":true,"usgs":true}],"preferred":true,"id":940871,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Weinstein, David A.","contributorId":206027,"corporation":false,"usgs":false,"family":"Weinstein","given":"David","email":"","middleInitial":"A.","affiliations":[{"id":12722,"text":"Cornell University","active":true,"usgs":false}],"preferred":false,"id":940872,"contributorType":{"id":1,"text":"Authors"},"rank":4}]}} ,{"id":70267387,"text":"70267387 - 2025 - Linking permafrost to the abundance, biomass, and energy density of fish in Arctic headwater streams","interactions":[],"lastModifiedDate":"2025-05-21T14:10:33.157869","indexId":"70267387","displayToPublicDate":"2025-05-13T08:59:33","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1475,"text":"Ecosphere","active":true,"publicationSubtype":{"id":10}},"title":"Linking permafrost to the abundance, biomass, and energy density of fish in Arctic headwater streams","docAbstract":"Permafrost thaw alters groundwater flow, river hydrology, stream-catchment interactions, and the availability of carbon and nutrients in headwater streams. The impact of permafrost on watershed hydrology and biogeochemistry of headwater streams has been demonstrated, but there is little understanding of how permafrost influences fish in these ecosystems. We examined relations among permafrost characteristics, the resulting changes in water temperature, stream hydrology (e.g., discharge flashiness), and macroinvertebrates, with the abundance, biomass, and energy density of juvenile Dolly Varden (Salvelinus malma) and Arctic Grayling (Thymallus arcticus) across 10 headwater streams in northwestern Alaska. Macroinvertebrate density was driven by concentrations of dissolved carbon and nutrients supporting stream food webs. Dolly Varden abundance was primarily related to water temperature with fewer fish in warmer streams, whereas Dolly Varden energy density decreased with the flashiness of the headwater streams. Dolly Varden biomass was related to both temperature and bottom-up food web effects. The energy density of Arctic Grayling decreased with warmer temperatures and discharge flashiness. These relations demonstrate the importance of terrestrial–aquatic connections in permafrost landscapes and indicate the complexity of landscape effects on fish. Because permafrost thaw is one of the most impactful changes occurring as the Arctic warms, an improved understanding of how stream temperature, hydrology, and bottom-up food web processes influence fish populations can aid forecasting of future conditions across the Arctic.
","language":"English","publisher":"Ecological Society of America","doi":"10.1002/ecs2.70270","usgsCitation":"Carey, M.P., Koch, J.C., O’Donnell, J.A., Poulin, B., and Zimmerman, C.E., 2025, Linking permafrost to the abundance, biomass, and energy density of fish in Arctic headwater streams: Ecosphere, v. 16, no. 5, e70270, 20 p., https://doi.org/10.1002/ecs2.70270.","productDescription":"e70270, 20 p.","ipdsId":"IP-168519","costCenters":[{"id":65299,"text":"Alaska Science Center Ecosystems","active":true,"usgs":true}],"links":[{"id":486925,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1002/ecs2.70270","text":"Publisher Index Page"},{"id":486281,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Alaska","otherGeospatial":"Noatak National Preserve","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -164,\n 69\n ],\n [\n -164,\n 66.7\n ],\n [\n -156,\n 66.7\n ],\n [\n -156,\n 69\n ],\n [\n -164,\n 69\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"16","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-13","publicationStatus":"PW","contributors":{"authors":[{"text":"Carey, Michael P. 0000-0002-3327-8995 mcarey@usgs.gov","orcid":"https://orcid.org/0000-0002-3327-8995","contributorId":5397,"corporation":false,"usgs":true,"family":"Carey","given":"Michael","email":"mcarey@usgs.gov","middleInitial":"P.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":117,"text":"Alaska Science Center Biology WTEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":938061,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Koch, Joshua C. 0000-0001-7180-6982 jkoch@usgs.gov","orcid":"https://orcid.org/0000-0001-7180-6982","contributorId":202532,"corporation":false,"usgs":true,"family":"Koch","given":"Joshua","email":"jkoch@usgs.gov","middleInitial":"C.","affiliations":[{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":938062,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"O’Donnell, Jonathan A. 0000-0001-7031-9808","orcid":"https://orcid.org/0000-0001-7031-9808","contributorId":191423,"corporation":false,"usgs":false,"family":"O’Donnell","given":"Jonathan","email":"","middleInitial":"A.","affiliations":[],"preferred":false,"id":938063,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Poulin, Brett 0000-0002-5555-7733","orcid":"https://orcid.org/0000-0002-5555-7733","contributorId":260893,"corporation":false,"usgs":false,"family":"Poulin","given":"Brett","affiliations":[{"id":52706,"text":"Department of Environmental Toxicology, University of California Davis, Davis, CA 95616, USA","active":true,"usgs":false}],"preferred":false,"id":938064,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Zimmerman, Christian E. 0000-0002-3646-0688 czimmerman@usgs.gov","orcid":"https://orcid.org/0000-0002-3646-0688","contributorId":410,"corporation":false,"usgs":true,"family":"Zimmerman","given":"Christian","email":"czimmerman@usgs.gov","middleInitial":"E.","affiliations":[{"id":120,"text":"Alaska Science Center Water","active":true,"usgs":true},{"id":116,"text":"Alaska Science Center Biology MFEB","active":true,"usgs":true},{"id":114,"text":"Alaska Science Center","active":true,"usgs":true}],"preferred":true,"id":938065,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70266760,"text":"sir20245133 - 2025 - Using the D-Claw software package to model lahars in the Middle Fork Nooksack River drainage and beyond, Mount Baker, Washington","interactions":[],"lastModifiedDate":"2025-07-03T14:16:54.133347","indexId":"sir20245133","displayToPublicDate":"2025-05-12T15:08:17","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":334,"text":"Scientific Investigations Report","code":"SIR","onlineIssn":"2328-0328","printIssn":"2328-031X","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2024-5133","displayTitle":"Using the D-Claw Software Package to Model Lahars in the Middle Fork Nooksack River Drainage and Beyond, Mount Baker, Washington","title":"Using the D-Claw software package to model lahars in the Middle Fork Nooksack River drainage and beyond, Mount Baker, Washington","docAbstract":"Lahars, or volcanic mudflows, are the most hazardous eruption-related phenomena that will affect communities living along rivers that originate on Mount Baker. In the past 15,000 years, the largest lahars from Mount Baker have affected the Middle Fork Nooksack River drainage and beyond. Here we use the physics-based D-Claw software package to model nine lahar scenarios that are initiated as water-saturated landslides between Sherman Crater and the Roman Wall on the Mount Baker edifice and flow down the Middle Fork Nooksack River. The scenarios range in volume from 1 to 260 million cubic meters and have an initial hydraulic permeability from 10−12 to 10−10 meters squared. Model output includes data such as flow depth, velocity, runout distance, area inundated, arrival time, and sediment concentration as well as information that allows scientists to calculate other important hydrologic characteristics such as lahar discharge. These data are important to officials who have the responsibility to plan for, or take mitigation measures against, future Mount Baker lahars. To check the validity of the D-Claw results, we compare the scenarios to known geologic information. We also compare D-Claw results with empirical models that have been used in the past to determine potential inundation areas, runout distances, and arrival times. These comparisons highlight similarities and differences between empirical and physics-based models. We also present D-Claw scenario-based animations to help scientists, officials, and lay people alike to visualize how future lahars could affect communities.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/sir20245133","usgsCitation":"Gardner, C.A., Benage, M.C., Cannon, C., and George, D.L., 2025, Using the D-Claw software package to model lahars in the Middle Fork Nooksack River drainage and beyond, Mount Baker, Washington: U.S. Geological Survey Scientific Investigations Report 2024–5133, 47 p., https://doi.org/10.3133/sir20245133.","productDescription":"Report: vii, 47 p.; 9 Animation Videos; Data Release","numberOfPages":"47","ipdsId":"IP-151680","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"links":[{"id":485743,"rank":13,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioC2.mp4","text":"Appendix 4 - Scenario C2","size":"35.9 MB","description":"Scenario C2","linkHelpText":"- Scenario C2"},{"id":485742,"rank":12,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioB3.mp4","text":"Appendix 4 - Scenario B3","size":"47 MB","description":"Scenario B3","linkHelpText":"- Scenario B3"},{"id":485741,"rank":11,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioB2.mp4","text":"Appendix 4 - Scenario B2","size":"37.6 MB","description":"Scenario B2","linkHelpText":"- Scenario B2"},{"id":485740,"rank":10,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioB1.mp4","text":"Appendix 4 - Scenario B1","size":"25.6 MB","description":"Scenario B1","linkHelpText":"- Scenario B1"},{"id":485739,"rank":9,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioA3.mp4","text":"Appendix 4 - Scenario A3","size":"50.4 MB","description":"Scenario A3","linkHelpText":"- Scenario A3"},{"id":485737,"rank":7,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioA1.mp4","text":"Appendix 4 - Scenario A1","size":"35.4 MB","description":"Scenario A1","linkHelpText":"- Scenario A1"},{"id":485736,"rank":6,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P1PEX7FS","text":"USGS data release","description":"George, D.L., Cannon, C.M., Benage, M.C., and Gardner, C.A., 2025, Simulated lahar extents and dynamics in the Middle Fork Nooksack River drainage, resulting from hypothetical landslide sources on the western summit of Mount Baker, Washington: U.S. Geological Survey data release, https://doi.org/10.5066/P1PEX7FS.","linkHelpText":"Simulated lahar extents and dynamics in the Middle Fork Nooksack River drainage, resulting from hypothetical landslide sources on the western summit of Mount Baker, Washington"},{"id":485734,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/sir/2024/5133/images"},{"id":485733,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133.XML","description":"SIR 2024-5133 XML"},{"id":485731,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133.pdf","text":"Report","size":"12 MB","linkFileType":{"id":1,"text":"pdf"},"description":"SIR 2024-5133 PDF"},{"id":485730,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/sir/2024/5133/coverthb.jpg"},{"id":485745,"rank":15,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioE2.mp4","text":"Appendix 4 - Scenario E2","size":"22.1 MB","description":"Scenario E2","linkHelpText":"- Scenario E2"},{"id":485744,"rank":14,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioD2.mp4","text":"Appendix 4 - Scenario D2","size":"26.5 MB","description":"Scenario D2","linkHelpText":"- Scenario D2"},{"id":485732,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/sir20245133/full","linkFileType":{"id":5,"text":"html"},"description":"SIR 2024-5133 HTML"},{"id":485738,"rank":8,"type":{"id":3,"text":"Appendix"},"url":"https://pubs.usgs.gov/sir/2024/5133/sir20245133_app4_scenarioA2.mp4","text":"Appendix 4 - Scenario A2","size":"41.7 MB","description":"Scenario A2","linkHelpText":"- Scenario A2"},{"id":485848,"rank":16,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118573.htm","linkFileType":{"id":5,"text":"html"}}],"country":"United States","state":"Washington","otherGeospatial":"Middle Fork Nooksack River, Mount Baker","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -121.667,\n 49\n ],\n [\n -122.667,\n 49\n ],\n [\n -122.667,\n 48.6667\n ],\n [\n -121.667,\n 48.6667\n ],\n [\n -121.667,\n 49\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","contact":"David A. Johnston Cascades Volcano Observatory
U.S. Geological Survey
1300 SE Cardinal Court
Building 10, Suite 100
Vancouver, WA 98683
Email: askCVO@usgs.gov
","tableOfContents":"Protecting lives and livelihoods during volcanic eruptions is the key challenge in volcanology, conducted primarily by volcano monitoring and emergency management organisations, but it is complicated by scarce knowledge of how communities respond in times of crisis. Social sensing is a rapidly developing practice that can be adapted for volcanology. Here we use social sensing of Twitter (currently known as X) posts to track changes in social action and reaction throughout the 2018 eruption of Kīlauea on the island of Hawai`i. The volume of relevant posts very rapidly increases in early May, coincident with the beginning of the eruption; automated sentiment analysis shows a simultaneous shift towards more negative emotions being expressed in post text. Substantial negative trends in sentiment are evident in reaction to high-impact events, including the destruction of a popular residential area and injuries sustained by tourists viewing the eruption. Topics of local Twitter conversation reveal societal actions, including the sharing of hazard warnings, mitigation actions, and aid announcements. Temporal trends in societal actions reflect patterns in volcanic activity (e.g. the peak and waning of eruptive activity), civil protection actions (e.g. risk mitigation actions and the communication of official warnings), and socioeconomic pressures (e.g. the destruction of homes). Local tweets detailing eruption damage and disruption display a similar temporal trend to independent estimates of the number of buildings in contact with lava. We show how hazard and risk information is discussed and reacted to on Twitter, which helps inform our understanding of community response actions and aids situational awareness, and outline how our approach could be adapted for use in real time.
","language":"English","publisher":"European Geosciences Union","doi":"10.5194/nhess-25-1681-2025","usgsCitation":"Hickey, J., Young, J., Spruce, M., Pandit, R., Williams, H., Arthur, R., Stovall, W., and Head, M., 2025, Social sensing a volcanic eruption: Application to Kīlauea, 2018: Natural Hazards and Earth System Sciences, v. 25, no. 5, p. 1681-1696, https://doi.org/10.5194/nhess-25-1681-2025.","productDescription":"16 p.","startPage":"1681","endPage":"1696","ipdsId":"IP-168133","costCenters":[{"id":508,"text":"Office of the AD Hazards","active":true,"usgs":true}],"links":[{"id":488089,"rank":2,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.5194/nhess-25-1681-2025","text":"Publisher Index Page"},{"id":486513,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Hawaii","otherGeospatial":"Kilauea Volcano","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -155.34909539011298,\n 19.523234716050013\n ],\n [\n -155.34909539011298,\n 19.22327113116394\n ],\n [\n -154.805338823834,\n 19.22327113116394\n ],\n [\n -154.805338823834,\n 19.523234716050013\n ],\n [\n -155.34909539011298,\n 19.523234716050013\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"25","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Hickey, James","contributorId":355777,"corporation":false,"usgs":false,"family":"Hickey","given":"James","affiliations":[{"id":84830,"text":"Department of Earth and Environmental Sciences, University of Exeter, UK","active":true,"usgs":false}],"preferred":false,"id":938130,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Young, James","contributorId":355778,"corporation":false,"usgs":false,"family":"Young","given":"James","affiliations":[{"id":84831,"text":"Department of Computer Science, University of Exeter, UK","active":true,"usgs":false}],"preferred":false,"id":938131,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Spruce, Michelle","contributorId":355779,"corporation":false,"usgs":false,"family":"Spruce","given":"Michelle","affiliations":[{"id":84833,"text":"Liverpool Business School, Liverpool John Moores University, UK","active":true,"usgs":false}],"preferred":false,"id":938132,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Pandit, Ravi","contributorId":355780,"corporation":false,"usgs":false,"family":"Pandit","given":"Ravi","affiliations":[{"id":84834,"text":"Institute for Data Science and Artificial Intelligence, University of Exeter, UK","active":true,"usgs":false}],"preferred":false,"id":938133,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Williams, Hywel","contributorId":355781,"corporation":false,"usgs":false,"family":"Williams","given":"Hywel","affiliations":[{"id":84831,"text":"Department of Computer Science, University of Exeter, UK","active":true,"usgs":false}],"preferred":false,"id":938134,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Arthur, Rudy","contributorId":355782,"corporation":false,"usgs":false,"family":"Arthur","given":"Rudy","affiliations":[{"id":84831,"text":"Department of Computer Science, University of Exeter, UK","active":true,"usgs":false}],"preferred":false,"id":938135,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Stovall, Wendy K. 0000-0003-2518-2595","orcid":"https://orcid.org/0000-0003-2518-2595","contributorId":214673,"corporation":false,"usgs":true,"family":"Stovall","given":"Wendy K.","affiliations":[{"id":617,"text":"Volcano Science Center","active":true,"usgs":true}],"preferred":true,"id":938136,"contributorType":{"id":1,"text":"Authors"},"rank":7},{"text":"Head, Matthew","contributorId":331805,"corporation":false,"usgs":false,"family":"Head","given":"Matthew","email":"","affiliations":[{"id":16984,"text":"University of Illinois at Urbana-Champaign","active":true,"usgs":false}],"preferred":false,"id":938137,"contributorType":{"id":1,"text":"Authors"},"rank":8}]}} ,{"id":70266906,"text":"70266906 - 2025 - Assessing potential collateral effects on amphibians from insecticide applications for flea control and plague mitigation","interactions":[],"lastModifiedDate":"2025-05-15T14:58:27.853948","indexId":"70266906","displayToPublicDate":"2025-05-12T09:46:05","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":2980,"text":"PLoS ONE","active":true,"publicationSubtype":{"id":10}},"title":"Assessing potential collateral effects on amphibians from insecticide applications for flea control and plague mitigation","docAbstract":"Ideal disease mitigation measures for wildlife are safe and benign for target species, non-target organisms, the environment, and humans. Identifying collateral (i.e., unintended) effects is a key consideration in implementing such actions. Deltamethrin dust and fipronil-laced baits represent a group of insecticides that target fleas (pulicides) and are used to control flea (Siphonaptera) vectors of the plague bacterium Yersinia pestis to protect prairie dogs (Cynomys spp.) and their plague-susceptible obligate predators, endangered black-footed ferrets (Mustela nigripes). A variety of animals use prairie dog burrows as refuge, which potentially exposes them to deltamethrin, and to fipronil and its metabolites in fecal pellets excreted by prairie dogs and other mammals that have eaten fipronil baits. We assessed the potential effects of deltamethrin and fipronil residues on survival, body mass, and activity of western tiger salamanders (Ambystoma mavortium), a burrow-inhabiting amphibian. Pulicides were applied at realistic concentrations in mesocosms mimicking burrows. Treatments included (1) deltamethrin dust and non-treated prairie dog fecal pellets, (2) prairie dog fecal pellets containing fipronil and fipronil sulfone, and (3) un-treated prairie dog fecal pellets as controls. All 29 salamanders survived the experiment. We did not detect pulicide residues in any control salamanders. Fipronil sulfone was detected in tissues from 3 of 10 salamanders in the fipronil treatment and deltamethrin was detected in tissues from 9 of 11 salamanders in the deltamethrin treatment. Salamanders were observed outside of burrows more frequently after treatments than before. Deltamethrin concentrations in whole body samples correlated positively with the amount of time salamanders were inside burrows. Acute, lethal effects were not detected, but uptake of deltamethrin and, to a lesser extent fipronil sulfone, into salamander tissues indicated the potential for long-term effects on this non-target species. Identifying potential collateral effects is an important aspect of evaluating mitigation actions implemented to protect endangered species.
","language":"English","publisher":"PLoS","doi":"10.1371/journal.pone.0320382","usgsCitation":"Eads, D.A., Shriner, S.A., Ellis, J.W., Cryan, P.M., Hladik, M.L., Dooley, G.P., and Muths, E., 2025, Assessing potential collateral effects on amphibians from insecticide applications for flea control and plague mitigation: PLoS ONE, v. 20, no. 5, e0320382, 15 p., https://doi.org/10.1371/journal.pone.0320382.","productDescription":"e0320382, 15 p.","ipdsId":"IP-160537","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":488598,"rank":1,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1371/journal.pone.0320382","text":"Publisher Index Page"},{"id":486312,"rank":0,"type":{"id":30,"text":"Data Release"},"url":"https://doi.org/10.5066/P9NR46X4","text":"USGS data release","linkHelpText":"Data on tiger salamander body mass, behavioral activity, and insecticide residues"},{"id":485994,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"volume":"20","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Eads, David A. 0000-0002-4247-017X deads@usgs.gov","orcid":"https://orcid.org/0000-0002-4247-017X","contributorId":173639,"corporation":false,"usgs":true,"family":"Eads","given":"David","email":"deads@usgs.gov","middleInitial":"A.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":false,"id":937098,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Shriner, Susan A.","contributorId":168690,"corporation":false,"usgs":false,"family":"Shriner","given":"Susan","email":"","middleInitial":"A.","affiliations":[{"id":13407,"text":"Colorado State Univ.","active":true,"usgs":false}],"preferred":false,"id":937099,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ellis, Jeremy W.","contributorId":212846,"corporation":false,"usgs":false,"family":"Ellis","given":"Jeremy","email":"","middleInitial":"W.","affiliations":[{"id":36589,"text":"USDA","active":true,"usgs":false}],"preferred":false,"id":937100,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Cryan, Paul M. 0000-0002-2915-8894 cryanp@usgs.gov","orcid":"https://orcid.org/0000-0002-2915-8894","contributorId":147942,"corporation":false,"usgs":true,"family":"Cryan","given":"Paul","email":"cryanp@usgs.gov","middleInitial":"M.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":937101,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Hladik, Michelle L. 0000-0002-0891-2712","orcid":"https://orcid.org/0000-0002-0891-2712","contributorId":221229,"corporation":false,"usgs":true,"family":"Hladik","given":"Michelle","middleInitial":"L.","affiliations":[{"id":154,"text":"California Water Science Center","active":true,"usgs":true}],"preferred":true,"id":937102,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Dooley, Gregory P.","contributorId":347021,"corporation":false,"usgs":false,"family":"Dooley","given":"Gregory","email":"","middleInitial":"P.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":937103,"contributorType":{"id":1,"text":"Authors"},"rank":6},{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":245922,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":937104,"contributorType":{"id":1,"text":"Authors"},"rank":7}]}} ,{"id":70267384,"text":"70267384 - 2025 - The complete mitochondrial genomes of the freshwater mussel Ortmanniana ligamentina (Lamarck, 1819): male and female mitotypes","interactions":[],"lastModifiedDate":"2025-05-21T14:17:25.275471","indexId":"70267384","displayToPublicDate":"2025-05-12T09:11:00","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":5471,"text":"Mitochondrial DNA Part B","active":true,"publicationSubtype":{"id":10}},"displayTitle":"The complete mitochondrial genomes of the freshwater mussel Ortmanniana ligamentina (Lamarck, 1819): male and female mitotypes","title":"The complete mitochondrial genomes of the freshwater mussel Ortmanniana ligamentina (Lamarck, 1819): male and female mitotypes","docAbstract":"Freshwater mussels of the Unionida order are important to freshwater ecosystems but are highly imperiled worldwide. Improving our understanding of these species is crucial to their continued conservation. Some Unionid mussels exhibit double uniparental inheritance (DUI) in which individuals have two mitochondrial genomes. Of those species with DUI, sequences of the female mitotype are most prevalent in genetic databases. Here, we demonstrate the ability to recover both mitotypes of Ortmanniana ligamentina (Lamarck, 1819) from a non-lethal collection method coupled with high-throughput sequencing. Increased male mitotype sequence representation facilitates understanding Unionid genetic diversity and development of molecular tools for species detection.
","language":"English","publisher":"Taylor & Francis","doi":"10.1080/23802359.2025.2500528","usgsCitation":"Klymus, K.E., Coombs, J., Ruiz-Ramos, D., Maloy, A., and Barnhart, C.M., 2025, The complete mitochondrial genomes of the freshwater mussel Ortmanniana ligamentina (Lamarck, 1819): male and female mitotypes: Mitochondrial DNA Part B, v. 10, no. 6, p. 430-436, https://doi.org/10.1080/23802359.2025.2500528.","productDescription":"7 p.","startPage":"430","endPage":"436","ipdsId":"IP-169543","costCenters":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"links":[{"id":486910,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1080/23802359.2025.2500528","text":"Publisher Index Page"},{"id":486282,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Missouri, Pennsylvania","otherGeospatial":"Allegheny River, Saint Francis River","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -90.51182908381749,\n 37.19162849485569\n ],\n [\n -90.51182908381749,\n 37.14017784562941\n ],\n [\n -90.46325971350004,\n 37.14017784562941\n ],\n [\n -90.46325971350004,\n 37.19162849485569\n ],\n [\n -90.51182908381749,\n 37.19162849485569\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n },\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -79.42977164664136,\n 41.496369262616895\n ],\n [\n -79.61497330981219,\n 41.496369262616895\n ],\n [\n -79.61497330981219,\n 41.42903968922411\n ],\n [\n -79.42977164664136,\n 41.42903968922411\n ],\n [\n -79.42977164664136,\n 41.496369262616895\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"10","issue":"6","noUsgsAuthors":false,"publicationDate":"2025-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Klymus, Katy E. 0000-0002-8843-6241 kklymus@usgs.gov","orcid":"https://orcid.org/0000-0002-8843-6241","contributorId":5043,"corporation":false,"usgs":true,"family":"Klymus","given":"Katy","email":"kklymus@usgs.gov","middleInitial":"E.","affiliations":[{"id":192,"text":"Columbia Environmental Research Center","active":true,"usgs":true}],"preferred":true,"id":938050,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Coombs, Jason","contributorId":299021,"corporation":false,"usgs":false,"family":"Coombs","given":"Jason","affiliations":[{"id":37062,"text":"UMASS","active":true,"usgs":false}],"preferred":false,"id":938052,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Ruiz-Ramos, Dannise","contributorId":332474,"corporation":false,"usgs":false,"family":"Ruiz-Ramos","given":"Dannise","affiliations":[{"id":78382,"text":"formerly Columbia Environmental Research Center","active":true,"usgs":false}],"preferred":false,"id":938051,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Maloy, Aaron","contributorId":343773,"corporation":false,"usgs":false,"family":"Maloy","given":"Aaron","email":"","affiliations":[{"id":6661,"text":"US Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":938053,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Barnhart, Christopher M.","contributorId":331084,"corporation":false,"usgs":false,"family":"Barnhart","given":"Christopher","email":"","middleInitial":"M.","affiliations":[{"id":16806,"text":"Missouri State University","active":true,"usgs":false}],"preferred":false,"id":938054,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267484,"text":"70267484 - 2025 - A framework for guiding management decisions for amphibians in an uncertain future","interactions":[],"lastModifiedDate":"2026-03-17T14:12:06.671127","indexId":"70267484","displayToPublicDate":"2025-05-12T09:04:58","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":1,"text":"Federal Government Series"},"title":"A framework for guiding management decisions for amphibians in an uncertain future","docAbstract":"Managing species in a rapidly changing climate requires knowledge of how species will respond to climate change and other threats while simultaneously developing management actions to reduce threats. Amphibians are one of the most threatened taxa on earth and often serve as the ‘canary in the coalmine’ for the health of ecosystems that countless other species and humans rely on. To understand the status of and guide management for the boreal toad (Anaxyrus boreas boreas), an imperiled amphibian species in the North Central region, we coproduced several products with the Boreal Toad Conservation Team. These products included 1) reconstructed seasonal hydrology patterns for historical boreal toad breeding wetlands and high elevation watersheds in the Southern Rocky Mountain Region (SRMR) from remotely sensed data, 2) current and future predictions of drying rates for historical breeding wetlands, 3) current and future predictions on the status of the boreal toad in the SRMR, and 4) a web tool to guide management actions. While the boreal toad is considered a ‘data rich’ species given data collection efforts that span multiple decades, many amphibian species are considered ‘data poor’, meaning managers lack data on the biology, ecology, or status of the species needed to make sound decisions. To address this knowledge gap, we also quantified drying patterns across watersheds for two ‘data poor’ species in the North Central region at risk from climate change: the Great Basin spadefoot toad (Spea intermontana) and the wood frog (Lithobates sylvaticus). These new data can guide management decisions for these species by allowing managers to understand habitat changes with respect to water availability, a crucial element for amphibian survival and persistence. Together, these products demonstrate how cutting-edge technology and analytical methods can produce a range of useful information to support amphibian conservation.
","language":"English","publisher":"Nrrth Central Climate Adaptation Center","usgsCitation":"Kissel, A.M., Muths, E., Lacey, M., Popescu, V.D., Dyck, M., and Littlefield, C., 2025, A framework for guiding management decisions for amphibians in an uncertain future, 56 p.","productDescription":"56 p.","ipdsId":"IP-174467","costCenters":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"links":[{"id":486563,"rank":1,"type":{"id":15,"text":"Index Page"},"url":"https://cascprojects.org/#/project/4f83509de4b0e84f60868124/6009c26fd34e162231fb2333","linkFileType":{"id":5,"text":"html"}},{"id":501210,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado, New Mexico, Wyoming","otherGeospatial":"southern Rocky Mountain region","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -108,\n 41.25\n ],\n [\n -108,\n 36.5\n ],\n [\n -105,\n 36.5\n ],\n [\n -105,\n 41.25\n ],\n [\n -108,\n 41.25\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Kissel, Amanda Marie 0000-0002-6346-7455","orcid":"https://orcid.org/0000-0002-6346-7455","contributorId":334356,"corporation":false,"usgs":true,"family":"Kissel","given":"Amanda","email":"","middleInitial":"Marie","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":938369,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Muths, Erin L. 0000-0002-5498-3132","orcid":"https://orcid.org/0000-0002-5498-3132","contributorId":245922,"corporation":false,"usgs":true,"family":"Muths","given":"Erin L.","affiliations":[{"id":291,"text":"Fort Collins Science Center","active":true,"usgs":true}],"preferred":true,"id":938370,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Lacey, Mae","contributorId":355913,"corporation":false,"usgs":false,"family":"Lacey","given":"Mae","affiliations":[{"id":13470,"text":"Conservation Science Partners","active":true,"usgs":false}],"preferred":false,"id":938371,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Popescu, Viorel D.","contributorId":169697,"corporation":false,"usgs":false,"family":"Popescu","given":"Viorel","email":"","middleInitial":"D.","affiliations":[],"preferred":false,"id":938372,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Dyck, Marissa","contributorId":355915,"corporation":false,"usgs":false,"family":"Dyck","given":"Marissa","affiliations":[{"id":16829,"text":"University of Victoria","active":true,"usgs":false}],"preferred":false,"id":938373,"contributorType":{"id":1,"text":"Authors"},"rank":5},{"text":"Littlefield, Caitlin","contributorId":352216,"corporation":false,"usgs":false,"family":"Littlefield","given":"Caitlin","affiliations":[],"preferred":false,"id":938374,"contributorType":{"id":1,"text":"Authors"},"rank":6}]}} ,{"id":70266500,"text":"ofr20251019 - 2025 - The feasibility of using lidar-derived digital elevation models for gravity data reduction","interactions":[],"lastModifiedDate":"2025-07-07T14:15:33.584578","indexId":"ofr20251019","displayToPublicDate":"2025-05-12T08:40:00","publicationYear":"2025","noYear":false,"publicationType":{"id":18,"text":"Report"},"publicationSubtype":{"id":5,"text":"USGS Numbered Series"},"seriesTitle":{"id":330,"text":"Open-File Report","code":"OFR","onlineIssn":"2331-1258","printIssn":"0196-1497","active":true,"publicationSubtype":{"id":5}},"seriesNumber":"2025-1019","displayTitle":"The Feasibility of Using Lidar-Derived Digital Elevation Models for Gravity Data Reduction","title":"The feasibility of using lidar-derived digital elevation models for gravity data reduction","docAbstract":"Gravity data require submeter elevation accuracy for data processing, and differential global navigation satellite system (dGNSS) equipment is commonly used to acquire three-dimensional positional data to achieve such accuracy. However, lidar (light detection and ranging) data are commonly used to develop digital elevation models (DEMs) of Earth’s surface. Therefore, using elevations from lidar-derived DEMs for gravity-data acquisition and reduction may improve field efficiency and reduce cost. This study examines the feasibility of using DEMs for gravity-data reduction by comparing dGNSS elevation data from 435 gravity stations in Michigan, Wyoming, and Colorado with their respective DEM elevations. The results show that the average difference between DEM and dGNSS elevations is 13 centimeters (cm) and that 93 percent of those differences are less than 50 cm, even in areas with steep terrain. Because an elevation discrepancy of 50 cm corresponds to an error of roughly 0.1 milligals (mGal) in the simple Bouguer gravity anomaly, the results suggest that lidar-derived DEMs are a viable source for acquiring the elevation data needed to process gravity data, thus improving both the cost and efficiency of data collection for regional surveys where an accuracy of less than 1.0 mGal is desired.
","language":"English","publisher":"U.S. Geological Survey","publisherLocation":"Reston, VA","doi":"10.3133/ofr20251019","programNote":"Mineral Resources Program","usgsCitation":"Murchek, J.T., Drenth, B.J., Reitman, J.J., Anderson, E.D., Magnin, B.P., and DeGraff, J.M., 2025, The feasibility of using lidar-derived digital elevation models for gravity data reduction (ver. 1.1, July 2025): U.S. Geological Survey Open-File Report 2025–1019, 33 p., https://doi.org/10.3133/ofr20251019.","productDescription":"vii, 33 p.","numberOfPages":"33","onlineOnly":"Y","additionalOnlineFiles":"N","ipdsId":"IP-163043","costCenters":[{"id":312,"text":"Geology, Minerals, Energy, and Geophysics Science Center","active":true,"usgs":true},{"id":35995,"text":"Geology, Geophysics, and Geochemistry Science Center","active":true,"usgs":true}],"links":[{"id":491565,"rank":1,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/of/2025/1019/coverthb2.jpg"},{"id":491633,"rank":6,"type":{"id":36,"text":"NGMDB Index Page"},"url":"https://ngmdb.usgs.gov/Prodesc/proddesc_118572.htm"},{"id":491634,"rank":2,"type":{"id":11,"text":"Document"},"url":"https://pubs.usgs.gov/of/2025/1019/ofr20251019.pdf","text":"Report","size":"12.3 MB","linkFileType":{"id":1,"text":"pdf"},"description":"OFR 2025-1019 PDF"},{"id":491636,"rank":4,"type":{"id":31,"text":"Publication XML"},"url":"https://pubs.usgs.gov/of/2025/1019/ofr20251019.XML","linkFileType":{"id":8,"text":"xml"},"description":"OFR 2025-1019 XML"},{"id":491635,"rank":3,"type":{"id":39,"text":"HTML Document"},"url":"https://pubs.usgs.gov/publication/ofr20251019/full","text":"Report","linkFileType":{"id":5,"text":"html"},"description":"OFR 2025-1019 HTML"},{"id":491638,"rank":7,"type":{"id":25,"text":"Version History"},"url":"https://pubs.usgs.gov/of/2025/1019/versionHist.txt","size":"654 B","linkFileType":{"id":2,"text":"txt"}},{"id":491637,"rank":5,"type":{"id":34,"text":"Image Folder"},"url":"https://pubs.usgs.gov/of/2025/1019/images/"}],"edition":"Version 1.0: May 12, 2025; Version 1.1: July 1, 2025","contact":"Director, Energy and Minerals Mission Area
U.S. Geological Survey
12201 Sunrise Valley Drive
Reston, VA 20192-0002
Subterranean estuaries (STE) in salt marshes are biogeochemically active zones where interactions between terrestrial groundwater and seawater drive complex cycling of carbon and trace elements, influenced by mineral dissolution. These systems, characterized by fine-grained organic-rich peat overlying permeable coastal aquifers, play a crucial role as a blue carbon sink, yet their geochemical dynamics remain poorly understood. We investigated dissolved trace elements, carbon, silica, and radium isotopes in a salt marsh STE (Sage Lot Pond, Waquoit Bay, MA) over seasonal and annual cycles. Our results reveal that groundwater and estuarine water circulation through marsh peat and aquifer sediments leads to enrichments of dissolved organic and inorganic carbon (DOC and DIC), Si, Ba, and Mn, with variable source/sink behavior of Fe and net removal of U. Submarine groundwater discharge dominated Ba fluxes, whereas pore water drainage from marsh peat acted as the main sink for U and source of Si. Fe cycling was variable, with terrestrial Fe largely removed as groundwater passed through the STE, consistent with Fe-sulfide and amorphous phase formation. Radium isotope ratios identified two distinct subsurface flow pathways, influenced by metal-oxide cycling and organic matter breakdown. Si production was decoupled from DIC, suggesting Si originates from mineral alteration, whereas DIC results from both mineral weathering and microbial respiration. Silicate mineral alteration, coupled with marsh pore water drainage, accounts for up to 16% of annual DIC exports (66 g C m−2 y−1), highlighting the importance of STEs in coastal carbon and trace element cycling, especially as marshes face environmental change.
","language":"English","publisher":"American Geophysical Union","doi":"10.1029/2025JG008758","usgsCitation":"Tamborski, J., Eagle, M.J., Thorpe, M., Charette, M., Kurylyk, B., Rahman, S., Kroeger, K.D., O’Keefe Suttles, J.A., Mann, A.G., Brooks, T.W., and Wang, Z., 2025, Evidence of mineral alteration in a salt marsh subterranean estuary: Implications for carbon and trace element cycling: JGR Biogeosciences, v. 130, no. 5, e2025JG008758, 19 p., https://doi.org/10.1029/2025JG008758.","productDescription":"e2025JG008758, 19 p.","ipdsId":"IP-174900","costCenters":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":491003,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1029/2025jg008758","text":"Publisher Index Page"},{"id":490747,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Massachusetts","otherGeospatial":"Cape Cod, Sage Lot Pond salt marsh observatory","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -70.52056663105348,\n 41.559066095910765\n ],\n [\n -70.52056663105348,\n 41.55128306872197\n ],\n [\n -70.49785805589167,\n 41.55128306872197\n ],\n [\n -70.49785805589167,\n 41.559066095910765\n ],\n [\n -70.52056663105348,\n 41.559066095910765\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"130","issue":"5","noUsgsAuthors":false,"publicationDate":"2025-05-12","publicationStatus":"PW","contributors":{"authors":[{"text":"Tamborski, J.J.","contributorId":350271,"corporation":false,"usgs":false,"family":"Tamborski","given":"J.J.","affiliations":[{"id":36518,"text":"Old Dominion 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adriangreen@usgs.gov","orcid":"https://orcid.org/0000-0003-1689-8524","contributorId":4328,"corporation":false,"usgs":true,"family":"Mann","given":"Adrian","email":"adriangreen@usgs.gov","middleInitial":"G.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940387,"contributorType":{"id":1,"text":"Authors"},"rank":9},{"text":"Brooks, Thomas W. 0000-0002-0555-3398 wallybrooks@usgs.gov","orcid":"https://orcid.org/0000-0002-0555-3398","contributorId":5989,"corporation":false,"usgs":true,"family":"Brooks","given":"Thomas","email":"wallybrooks@usgs.gov","middleInitial":"W.","affiliations":[{"id":678,"text":"Woods Hole Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":940388,"contributorType":{"id":1,"text":"Authors"},"rank":10},{"text":"Wang, Z.A.","contributorId":350270,"corporation":false,"usgs":false,"family":"Wang","given":"Z.A.","affiliations":[{"id":83704,"text":"Woods Hole Oceanography Institution","active":true,"usgs":false}],"preferred":false,"id":940389,"contributorType":{"id":1,"text":"Authors"},"rank":11}]}} ,{"id":70265625,"text":"70265625 - 2025 - A geospatial analysis of water-quality threats from orphan wells in principal and secondary aquifers of the United States","interactions":[],"lastModifiedDate":"2025-04-14T16:22:56.080636","indexId":"70265625","displayToPublicDate":"2025-05-10T09:19:11","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":3352,"text":"Science of the Total Environment","active":true,"publicationSubtype":{"id":10}},"title":"A geospatial analysis of water-quality threats from orphan wells in principal and secondary aquifers of the United States","docAbstract":"Throughout the history of oil and gas production in the United States, millions of wells have been drilled for exploration and energy production. Hundreds of thousands of unplugged wells are no longer actively producing and are currently under orphan status, with no responsible party obligated for plugging. Orphan wells can pose threats to water resources by providing pathways for contaminants such as hydrocarbons and brines to migrate into water-supply aquifers. In this study, we investigate the potential threats to groundwater resources posed by orphan wells at the national scale. Water-quality data is extremely sparse in relation to orphan wells nationally and may not be suitable for identifying contamination from oil and gas development. We used geospatial and statistical methods to evaluate which principal and secondary aquifer systems may be most susceptible to contamination from orphan wells. Analysis involved three sets of susceptibility factors including: 1) factors related to the number and density of orphan wells; 2) factors that can threaten well integrity and contribute to transport of contaminants; and 3) factors related to groundwater withdrawal rates and the affected populations/communities in the event of water quality disturbances. From a dataset of 117,672 documented orphan wells, 64,203 fall within a principal aquifer system, while the remainder fall within a secondary aquifer system.
By assessing the combination of well integrity and hydrogeologic factors within these aquifer systems, five groupings of principal aquifers were identified, where groups ranged from aquifer systems with high numbers of orphan wells, multiple well integrity threats and high withdrawals, to aquifers with a relatively low number of orphan wells, limited well integrity threats and minimal water use. Three regions of the country emerge containing aquifers with higher susceptibility to contamination from orphan oil and gas wells. These regions include 1) The Appalachian Basin (including the Pennsylvanian Aquifer System), 2) The Gulf Coast Aquifers (including the Coastal Lowlands Aquifer system) and 3) The California Aquifers (including the California Coastal Basin Aquifer system). This work is the first multivariate geospatial investigation of orphan wells and groundwater resources on a national scale, and sheds light on which aquifers are most susceptible to groundwater contamination from orphan wells.
","language":"English","publisher":"ScienceDirect","doi":"10.1016/j.scitotenv.2025.179246","usgsCitation":"Woda, J., Haase, K., Gianoutsos, N.J., Jahn, K., and Gutchess, K., 2025, A geospatial analysis of water-quality threats from orphan wells in principal and secondary aquifers of the United States: Science of the Total Environment, v. 976, 179246, 20 p., https://doi.org/10.1016/j.scitotenv.2025.179246.","productDescription":"179246, 20 p.","ipdsId":"IP-170391","costCenters":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"links":[{"id":490096,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1016/j.scitotenv.2025.179246","text":"Publisher Index Page"},{"id":484512,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United 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States\"}}]}","volume":"976","noUsgsAuthors":false,"publicationStatus":"PW","contributors":{"authors":[{"text":"Woda, Joshua 0000-0002-2932-8013","orcid":"https://orcid.org/0000-0002-2932-8013","contributorId":290172,"corporation":false,"usgs":true,"family":"Woda","given":"Joshua","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933137,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Haase, Karl B. 0000-0002-6897-6494","orcid":"https://orcid.org/0000-0002-6897-6494","contributorId":216317,"corporation":false,"usgs":true,"family":"Haase","given":"Karl B.","affiliations":[{"id":37277,"text":"WMA - Earth System Processes Division","active":true,"usgs":true},{"id":436,"text":"National Research Program - Eastern Branch","active":true,"usgs":true}],"preferred":true,"id":933138,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Gianoutsos, Nicholas J. 0000-0002-6510-6549 ngianoutsos@usgs.gov","orcid":"https://orcid.org/0000-0002-6510-6549","contributorId":3607,"corporation":false,"usgs":true,"family":"Gianoutsos","given":"Nicholas","email":"ngianoutsos@usgs.gov","middleInitial":"J.","affiliations":[{"id":164,"text":"Central Energy Resources Science Center","active":true,"usgs":true},{"id":241,"text":"Eastern Energy Resources Science Center","active":true,"usgs":true}],"preferred":true,"id":933139,"contributorType":{"id":1,"text":"Authors"},"rank":3},{"text":"Jahn, Kalle 0000-0002-4976-0137","orcid":"https://orcid.org/0000-0002-4976-0137","contributorId":333053,"corporation":false,"usgs":true,"family":"Jahn","given":"Kalle","email":"","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933140,"contributorType":{"id":1,"text":"Authors"},"rank":4},{"text":"Gutchess, Kristina 0000-0002-9745-5049","orcid":"https://orcid.org/0000-0002-9745-5049","contributorId":353190,"corporation":false,"usgs":true,"family":"Gutchess","given":"Kristina","affiliations":[{"id":474,"text":"New York Water Science Center","active":true,"usgs":true}],"preferred":true,"id":933141,"contributorType":{"id":1,"text":"Authors"},"rank":5}]}} ,{"id":70267797,"text":"70267797 - 2025 - Identification of representative earthquakes for probabilistic tsunami hazard analysis (PTHA) using earthquake rupture forecasts and machine learning","interactions":[],"lastModifiedDate":"2025-06-02T14:20:21.988597","indexId":"70267797","displayToPublicDate":"2025-05-10T09:13:44","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":1803,"text":"Geophysical Journal International","active":true,"publicationSubtype":{"id":10}},"title":"Identification of representative earthquakes for probabilistic tsunami hazard analysis (PTHA) using earthquake rupture forecasts and machine learning","docAbstract":"As probabilistic tsunami hazard analysis (PTHA) focuses more on assessments for localized, populous regions, techniques are needed to identify a subsample of representative earthquake ruptures to make the computational requirements for producing high-resolution hazard maps tractable. Moreover, the greatest epistemic uncertainty in seismic PTHA is related to source characterization, which is often poorly defined and subjective. We address these two salient issues by applying streamlined earthquake rupture forecasts (ERFs), based on combinatorial optimization methods, to an unsupervised machine learning workflow for identifying representative ruptures. ERFs determine the optimal distribution of a millennia-scale sample of earthquakes by inverting the observed slip rate on major faults. We use two previously developed combinatorial optimization ERFs, integer programming and greedy sequential, to produce the optimal location of ruptures with seismic moments sampled from a regional Gutenberg–Richter magnitude–frequency distribution. These ruptures in turn are used to calculate peak nearshore tsunami amplitude, using computationally efficient tsunami Green's functions. An unsupervised machine learning workflow is then used to identify a small subsample of the earthquakes input to ERFs for onshore PTHA analysis. We eliminate epistemic uncertainty related to source distribution under traditional PTHA analysis; in its place, a quantifiable, less subjective and generally smaller uncertainty related to the input to ERFs is included. The Nankai subduction zone is used as a test case, where previous ERFs have been conducted. Results indicate that the locations of representative earthquakes are sensitive to choice of magnitude–area relation and to whether a minimum cumulative stress objective is imposed on the fault. In general, incorporating ERFs into PTHA provide a physically self-consistent method to incorporate fault slip information in determining representative earthquakes for onshore PTHA, eliminating a major source of epistemic uncertainty.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/gji/ggaf173","usgsCitation":"Geist, E.L., and Parsons, T.E., 2025, Identification of representative earthquakes for probabilistic tsunami hazard analysis (PTHA) using earthquake rupture forecasts and machine learning: Geophysical Journal International, v. 242, no. 1, ggaf173, 22 p., https://doi.org/10.1093/gji/ggaf173.","productDescription":"ggaf173, 22 p.","ipdsId":"IP-174860","costCenters":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"links":[{"id":490659,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/gji/ggaf173","text":"Publisher Index Page"},{"id":489360,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"Japan","otherGeospatial":"Nankai subduction zone","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n 131,\n 37\n ],\n [\n 131,\n 31\n ],\n [\n 139,\n 31\n ],\n [\n 139,\n 37\n ],\n [\n 131,\n 37\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"242","issue":"1","noUsgsAuthors":false,"publicationDate":"2025-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Geist, Eric L. 0000-0003-0611-1150","orcid":"https://orcid.org/0000-0003-0611-1150","contributorId":15543,"corporation":false,"usgs":true,"family":"Geist","given":"Eric","email":"","middleInitial":"L.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":938927,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Parsons, Thomas E. 0000-0002-0582-4338 tparsons@usgs.gov","orcid":"https://orcid.org/0000-0002-0582-4338","contributorId":2314,"corporation":false,"usgs":true,"family":"Parsons","given":"Thomas","email":"tparsons@usgs.gov","middleInitial":"E.","affiliations":[{"id":520,"text":"Pacific Coastal and Marine Science Center","active":true,"usgs":true}],"preferred":true,"id":938928,"contributorType":{"id":1,"text":"Authors"},"rank":2}]}} ,{"id":70267771,"text":"70267771 - 2025 - Antigone canadensis (Sandhill Crane) foraging patterns influenced by crop type, roost distance, and tillage intensity during spring and autumn migration at a primary stopover area","interactions":[],"lastModifiedDate":"2025-05-30T15:43:43.66654","indexId":"70267771","displayToPublicDate":"2025-05-10T08:38:34","publicationYear":"2025","noYear":false,"publicationType":{"id":2,"text":"Article"},"publicationSubtype":{"id":10,"text":"Journal Article"},"seriesTitle":{"id":9101,"text":"Ornithological Applications","printIssn":"0010-5422","active":true,"publicationSubtype":{"id":10}},"title":"Antigone canadensis (Sandhill Crane) foraging patterns influenced by crop type, roost distance, and tillage intensity during spring and autumn migration at a primary stopover area","docAbstract":"The San Luis Valley in Colorado, USA, an agriculturally dominated stopover area, is used by the Rocky Mountain population of Antigone canadensis tabida (Greater Sandhill Crane) and some midcontinental individuals of A. c. canadensis (Lesser Sandhill Crane) during migration. While the numbers of both subspecies are stable, the effects of continued water scarcity and declines in grain output on the energetics of cranes in the San Luis Valley are unclear. We conducted roadside counts of A. c. tabida and A. c. canadensis on agricultural fields to determine the effects of crop type, roost distance, and tillage intensity on their selection and abundance on crop fields. Antigone canadensis varied in their use of the San Luis Valley for foraging. In autumn, both subspecies selected barley and other grains over other crop types. In spring, cranes preferred to forage in barley fields, and selection declined as distance to roosts increased. Both subspecies also selected barley fields that were lightly or not tilled. We modeled covariates on abundance for A. c. tabida only and found that more cranes were found close to roosts early in the season in autumn. As the season progressed, the number of A. c. tabida increased as roost distance increased. In spring, abundance was influenced by an interaction between time and crop, with the highest numbers found on barley and pasture around mid-March. Our results suggest that A. canadensis may switch to other crop types as resources are depleted near roosts but appear to prefer to fly farther for grains. Grains that are left idle or moderately tilled and are located near roosts will help ensure A. canadensis are able to maintain adequate nutrient reserves at agriculturally dominated stopover areas during migration.
","language":"English","publisher":"Oxford Academic","doi":"10.1093/ornithapp/duaf027","collaboration":"U. S. Fish and Wildlife Service","usgsCitation":"Vanausdall, R., Kendall, W.L., and Collins, D., 2025, Antigone canadensis (Sandhill Crane) foraging patterns influenced by crop type, roost distance, and tillage intensity during spring and autumn migration at a primary stopover area: Ornithological Applications, v. 127, duaf027, 17 p., https://doi.org/10.1093/ornithapp/duaf027.","productDescription":"duaf027, 17 p.","ipdsId":"IP-170214","costCenters":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"links":[{"id":490643,"rank":0,"type":{"id":40,"text":"Open Access Publisher Index Page"},"url":"https://doi.org/10.1093/ornithapp/duaf027","text":"Publisher Index Page"},{"id":489266,"type":{"id":24,"text":"Thumbnail"},"url":"https://pubs.usgs.gov/thumbnails/outside_thumb.jpg"}],"country":"United States","state":"Colorado","otherGeospatial":"San Luis Valley","geographicExtents":"{\n \"type\": \"FeatureCollection\",\n \"features\": [\n {\n \"type\": \"Feature\",\n \"properties\": {},\n \"geometry\": {\n \"coordinates\": [\n [\n [\n -106.19980544186409,\n 37.483870494045064\n ],\n [\n -106.19980544186409,\n 36.996256317805006\n ],\n [\n -105.66654470738654,\n 36.996256317805006\n ],\n [\n -105.66654470738654,\n 37.483870494045064\n ],\n [\n -106.19980544186409,\n 37.483870494045064\n ]\n ]\n ],\n \"type\": \"Polygon\"\n }\n }\n ]\n}","volume":"127","noUsgsAuthors":false,"publicationDate":"2025-05-10","publicationStatus":"PW","contributors":{"authors":[{"text":"Vanausdall, Rachel A.","contributorId":356156,"corporation":false,"usgs":false,"family":"Vanausdall","given":"Rachel A.","affiliations":[{"id":6621,"text":"Colorado State University","active":true,"usgs":false}],"preferred":false,"id":938810,"contributorType":{"id":1,"text":"Authors"},"rank":1},{"text":"Kendall, William L. 0000-0003-0084-9891","orcid":"https://orcid.org/0000-0003-0084-9891","contributorId":204844,"corporation":false,"usgs":true,"family":"Kendall","given":"William","email":"","middleInitial":"L.","affiliations":[{"id":200,"text":"Coop Res Unit Seattle","active":true,"usgs":true}],"preferred":true,"id":938811,"contributorType":{"id":1,"text":"Authors"},"rank":2},{"text":"Collins, Daniel P.","contributorId":356157,"corporation":false,"usgs":false,"family":"Collins","given":"Daniel P.","affiliations":[{"id":36188,"text":"U.S. Fish and Wildlife Service","active":true,"usgs":false}],"preferred":false,"id":938812,"contributorType":{"id":1,"text":"Authors"},"rank":3}]}} ]}